An in-depth investigation of the microbiota and its virulence factors associated with severe udder cleft dermatitis lesions

Udder cleft dermatitis (UCD) is a skin condition affecting the anterior parts of the udder in dairy cattle. In the present study, we aimed to shed light on the microbiota in severe UCD lesions versus healthy udder skin by putting forward a taxonomic and functional profile based on a virulence factor analysis. Through shotgun metagenomic sequencing, we found a high proportion of bacteria in addition to a low abundance of archaea. A distinct clustering of healthy udder skin versus UCD lesion samples was shown by applying principal component analysis and (sparse) partial least squares analysis on the metagenomic data. Proteobacteria, Bacillota, and Actinomycetota were among the most abundant phyla in healthy udder skin samples. In UCD samples, Bacteroidota was the most abundant phylum. At genus level, Bifidobacterium spp. had the highest relative abundance in healthy skin samples, whereas Porphyromonas spp. and Corynebacterium spp. had the highest relative abundance in UCD samples. In the differential abundance analysis, Porphyromonas spp. and Bacteroides spp. were significantly differentially abundant in UCD samples, whereas Bifidobacterium spp., Staphylococcus sp. AntiMn-1, and Staphylococcus equorum were more commonly found in healthy samples. Moreover, the abundance of several treponeme phylotypes was significantly higher in lesion samples. The streptococcal cysteine protease speB was among the most abundant virulence factors present in severe UCD lesions, while a plethora of virulence factors such as the antitoxin relB were downregulated, possibly contributing to creating the ideal wound climate for the dysbiotic community. Network analysis showed healthy lesion samples had a large network ofpositive, correlations between the abundances of beneficial species such as Aerococcus urinaeequi and Bifidobacterium angulatum, indicating that the healthy skin microbiome forms an active protective bacterial network, which is disrupted in case of UCD. In UCD samples, a smaller microbial network mainly consisting of positive correlations between the abundances of Bacteroides fragilis and anaerobic Bacteroidota was exposed. Moreover, a high correlation between the taxonomic data and virulence factors was revealed, concurrently with 2 separate networks of microbes and virulence factors. One network, matching with the taxonomic findings in the healthy udder skin samples, showcased a community of harmless or beneficial bacteria, such as Bifidobacterium spp. and Butyrivibrio proteoclasticus, associated with hcnB, hcnC, relB, glyoxalase, and cupin 2. The other network, corresponding to UCD samples, consisted of pathogenic or facultative pathogenic and mainly anaerobic bacteria such as Treponema spp., Mycoplasmopsis spp., and bovine gammaherpesvirus 4, that correlated with virulence factors SpvB, fhaB, and haemagglutination activity domain-associated factor. Our results point toward a dysbiotic community with a notable decrease in diversity and evenness, with a loss of normal skin inhabitants and innocuous or useful species making way for predominantly anaerobic, facultative pathogens. The shift in the abundance of virulence factors such as fhaB and SpvB could play a role in the manifestation of a local micro-environment favorable to the microbiome associated with udder skin lesions. Lastly, the presence of specific networks between microbial species, and between microbes and virulence factors was shown.

HMOs Impact the Gut Microbiome of Children and Adults Starting from Low Predicted Daily Doses

Recent studies suggest that the dietary intake of human milk oligosaccharides (HMOs) provides health benefits from infancy up to adulthood. Thus far, beneficial changes in the adult gut microbiome have been observed at oral doses of 5-20 g/day of HMOs. Efficacy of lower doses has rarely been tested. We assessed four HMO molecular species-2'Fucosyllactose (2'FL), Lacto-N-neotetraose (LNnT), 3'Sialyllactose (3'SL), and 6'Sialyllactose (6'SL)-at predicted doses from 0.3 to 5 g/day for 6-year-old children and adults (n = 6 each), using ex vivo SIFR® technology (Cryptobiotix, Ghent, Belgium). This technology employing bioreactor fermentation on fecal samples enables us to investigate microbial fermentation products that are intractable in vivo given their rapid absorption/consumption in the human gut. We found that HMOs significantly increased short-chain fatty acids (SCFAs), acetate, propionate (in children/adults), and butyrate (in adults) from predicted doses of 0.3-0.5 g/day onwards, with stronger effects as dosing increased. The fermentation of 6'SL had the greatest effect on propionate, LNnT most strongly increased butyrate, and 2'FL and 3'SL most strongly increased acetate. An untargeted metabolomic analysis revealed that HMOs enhanced immune-related metabolites beyond SCFAs, such as aromatic lactic acids (indole-3-lactic acid/3-phenyllactic acid) and 2-hydroxyisocaproic acid, as well as gut-brain-axis-related metabolites (γ-aminobutyric acid/3-hydroxybutyric acid/acetylcholine) and vitamins. The effects of low doses of HMOs potentially originate from the highly specific stimulation of keystone species belonging to, for example, the Bifidobacteriaceae family, which had already significantly increased at doses of only 0.5 g/day LNnT (adults) and 1 g/day 2'FL (children/adults).

Mining the microbiome of Lake Afdera to gain insights into microbial diversity and biosynthetic potential

Microorganisms inhabiting hypersaline environments have received significant attention due to their ability to thrive under poly-extreme conditions, including high salinity, elevated temperatures and heavy metal stress. They are believed to possess biosynthetic gene clusters (BGCs) that encode secondary metabolites as survival strategy and offer potential biotechnological applications. In this study, we mined BGCs in shotgun metagenomic sequences generated from Lake Afdera, a hypersaline lake in the Afar Depression, Ethiopia. The microbiome of Lake Afdera is predominantly bacterial, with Acinetobacter (18.6%) and Pseudomonas (11.8%) being ubiquitously detected. A total of 94 distinct BGCs were identified in the metagenomic data. These BGCs are found to encode secondary metabolites with two main categories of functions: (i) potential pharmaceutical applications (nonribosomal peptide synthase NRPs, polyketide synthase, others) and (ii) miscellaneous roles conferring adaptation to extreme environment (bacteriocins, ectoine, others). Notably, NRPs (20.6%) and bacteriocins (10.6%) were the most abundant. Furthermore, our metagenomic analysis predicted gene clusters that enable microbes to defend against a wide range of toxic metals, oxidative stress and osmotic stress. These findings suggest that Lake Afdera is a rich biological reservoir, with the predicted BGCs playing critical role in the survival and adaptation of extremophiles.

Metagenomic profiling of viral and microbial communities from the pox lesions of lumpy skin disease virus and sheeppox virus-infected hosts

Introduction

It has been recognized that capripoxvirus infections have a strong cutaneous tropism with the manifestation of skin lesions in the form of nodules and scabs in the respective hosts, followed by necrosis and sloughing off. Considering that the skin microbiota is a complex community of commensal bacteria, fungi and viruses that are influenced by infections leading to pathological states, there is no evidence on how the skin microbiome is affected during capripoxvirus pathogenesis.

Methods

In this study, shotgun metagenomic sequencing was used to investigate the microbiome in pox lesions from hosts infected with lumpy skin disease virus and sheep pox virus.

Results

The analysis revealed a high degree of variability in bacterial community structures across affected skin samples, indicating the importance of specific commensal microorganisms colonizing individual hosts. The most common and abundant bacteria found in scab samples were Fusobacterium necrophorum, Streptococcus dysgalactiae, Helcococcus ovis and Trueperella pyogenes, irrespective of host. Bacterial reads belonging to the genera Moraxella, Mannheimia, Corynebacterium, Staphylococcus and Micrococcus were identified.

Discussion

This study is the first to investigate capripox virus-associated changes in the skin microbiome using whole-genome metagenomic profiling. The findings will provide a basis for further investigation into capripoxvirus pathogenesis. In addition, this study highlights the challenge of selecting an optimal bioinformatics approach for the analysis of metagenomic data in clinical and veterinary practice. For example, direct classification of reads using a kmer-based algorithm resulted in a significant number of systematic false positives, which may be attributed to the peculiarities of the algorithm and database selection. On the contrary, the process of de novo assembly requires a large number of target reads from the symbiotic microbial community. In this work, the obtained sequencing data were processed by three different approaches, including direct classification of reads based on k-mers, mapping of reads to a marker gene database, and de novo assembly and binning of metagenomic contigs. The advantages and disadvantages of these techniques and their practicality in veterinary settings are discussed in relation to the results obtained.

A comprehensive overview of microbiome data in the light of machine learning applications: categorization, accessibility, and future directions

Metagenomics, Metabolomics, and Metaproteomics have significantly advanced our knowledge of microbial communities by providing culture-independent insights into their composition and functional potential. However, a critical challenge in this field is the lack of standard and comprehensive metadata associated with raw data, hindering the ability to perform robust data stratifications and consider confounding factors. In this comprehensive review, we categorize publicly available microbiome data into five types: shotgun sequencing, amplicon sequencing, metatranscriptomic, metabolomic, and metaproteomic data. We explore the importance of metadata for data reuse and address the challenges in collecting standardized metadata. We also, assess the limitations in metadata collection of existing public repositories collecting metagenomic data. This review emphasizes the vital role of metadata in interpreting and comparing datasets and highlights the need for standardized metadata protocols to fully leverage metagenomic data's potential. Furthermore, we explore future directions of implementation of Machine Learning (ML) in metadata retrieval, offering promising avenues for a deeper understanding of microbial communities and their ecological roles. Leveraging these tools will enhance our insights into microbial functional capabilities and ecological dynamics in diverse ecosystems. Finally, we emphasize the crucial metadata role in ML models development.

Butyric Acid Supplementation Reduces Changes in the Taxonomic and Functional Composition of Gut Microbiota Caused by H. pylori Eradication Therapy

H. pylori eradication therapy leads to significant changes in the gut microbiome, including influence on the gut microbiome's functional potential. Probiotics are one of the most studied potential methods for reducing the microbiota-related consequences of antibiotics. However, the beneficial effects of probiotics are still under discussion. In addition, there are some concerns about the safety of probiotics, emphasizing the need for research of other therapeutic interventions. The aim of our study was to evaluate the influence of butyric acid+inulin supplements on gut microbiota changes (the gut microbiota composition, abundance of metabolic pathways, and gut resistome) caused by H. pylori eradication therapy.

MATERIALS AND METHODS

Twenty two H. pylori-positive patients, aged 19 to 64 years, were enrolled in the study and randomized into two treatment groups, as follows: (1) ECAB-14 (n = 11), with esomeprazole 20 mg, clarithromycin 500 mg, amoxicillin 1000 mg, and bismuthate tripotassium dicitrate 240 mg, twice daily, per os, for 14 days, and (2), ECAB-Z-14 (n = 11), with esomeprazole 20 mg, clarithromycin 500 mg, amoxicillin 1000 mg, and bismuthate tripotassium dicitrate 240 mg, twice daily, along with butyric acid+inulin (Zacofalk), two tablets daily, each containing 250 mg of butyric acid, and 250 mg of inulin, per os, for 14 days. Fecal samples were collected from each subject prior to eradication therapy (time point I), after the end of eradication therapy (time point II), and a month after the end of eradication therapy (time point III). The total DNA from the fecal samples was isolated for whole genome sequencing using the Illumina NextSeq 500 platform. Qualitative and quantitative changes in gut microbiota were assessed, including alpha and beta diversity, functional potential and antibiotic resistance gene profiling.

RESULTS

Gut microbiota alpha diversity significantly decreased compared with the baseline immediately after eradication therapy in both treatment groups (ECAB-14 and ECAB-Z-14). This diversity reached its baseline in the ECAB-Z-14 treatment group a month after the end of eradication therapy. However, in the ECAB-14 treatment arm, a reduction in the Shannon index was observed up to a month after the end of H. pylori eradication therapy. Fewer alterations in the gut microbiota functional potential were observed in the ECAB-Z-14 treatment group. The abundance of genes responsible for the metabolic pathway associated with butyrate production decreased only in the ECAB-14 treatment group. The prevalence of antibiotic-resistant genes in the gut microbiota increased significantly in both treatment groups by the end of treatment. However, more severe alterations were noted in the ECAB-14 treatment group.

CONCLUSIONS

H. pylori eradication therapy leads to taxonomic changes, a reduction in the alpha diversity index, and alterations in the functional potential of the gut microbiota and gut resistome. Taking butyric acid+inulin supplements during H. pylori eradication therapy could help maintain the gut microbiota in its initial state and facilitate its recovery after H. pylori eradication.

Host DNA depletion methods and genome-centric metagenomics of bovine hindmilk microbiome

Bovine mastitis is a multi-etiological and complex disease, resulting in serious economic consequences for dairy farmers and industry. In recent years, the microbiological evaluation of raw milk has been investigated in-depth using next-generation sequencing approaches such as metataxonomic analysis. Despite this, host DNA is a major concern in the shotgun metagenomic sequencing of microbial communities in milk samples, and it represents a big challenge. In this study, we aimed to evaluate different methods for host DNA depletion and/or microbial DNA enrichment and assess the use of PCR-based whole genome amplification in milk samples with high somatic cell count (SCC) by using short- and long-read sequencing technologies. Our results evidenced that DNA extraction performed differently in terms of host DNA removal, impacting metagenome composition and functional profiles.. Moreover, the ratio of SCC/bacteria ultimately impacts microbial DNA yield, and samples with low SCC (SCC below 100,000 cells/mL) are the most problematic. When milk samples with high SCC (SCC above 200,000 cells/mL) underwent multiple-displacement amplification (MDA), we successfully recovered high-quality metagenome-assembled genomes (MAGs), and long-read sequencing was feasible even for samples with low DNA concentration. By associating MDA and short-read sequencing, we recovered two times more MAGs than in untreated samples, and an ongoing co-infection not reported by traditional methods was detected for mastitis pathogen. Overall, this new approach will improve the detection of mastitis-associated microorganisms and make it possible to examine host-microbiome interactions in bovine mastitis.IMPORTANCENext-generation sequencing technologies have been widely used to gain new insights into the diversity of the microbial community of milk samples and dairy products for different purposes such as microbial safety, profiling of starter cultures, and host-microbiome interactions. Milk is a complex food matrix, and additionally, the presence of host nucleic acid sequences is considered a contaminant in untargeted high-throughput sequencing studies. Therefore, genomic-centric metagenomic studies of milk samples focusing on the health-disease status in dairy cattle are still scarce, which makes it difficult to evaluate the microbial ecophysiology of bovine hindmilk. This study provides an alternative method for genome-centric metagenome studies applied to hindmilk samples with high somatic cell content, which is indispensable to examining host-microbiome interactions in bovine mastitis.

Whole-genome shotgun sequencing unravels the influence of environmental microbial co-infections on the treatment efficacy for severe pediatric infectious diseases

Background

The microbiome plays a pivotal role in mediating immune deviation during the development of early-life viral infections. Recurrent infections in children are considered a risk factor for disease development. This study delves into the metagenomics of the microbiome in children suffering from severe infections, seeking to identify potential sources of these infections.

Aims

The aim of this study was to identify the specific microorganisms and factors that significantly influence the treatment duration in patients suffering from severe infections. We sought to understand how these microbial communities and other variables may affect the treatment duration and the use of antibiotics of these patients with severe infections.

Method

Whole-genome shotgun sequencing was conducted on samples collected from children aged 0-14 years with severe infections, admitted to the Pediatrics Department of Xiamen First Hospital. The Kraken2 algorithm was used for taxonomic identification from sequence reads, and linear mixed models were employed to identify significant microorganisms influencing treatment duration. Colwellia, Cryptococcus, and Citrobacter were found to significantly correlate with the duration of clinical treatment. Further analysis using propensity score matching (PSM) and rank-sum test identified clinical indicators significantly associated with the presence of these microorganisms.

Results

Using a linear mixed model after removed the outliers, we identified that the abundance of Colwellia, Cryptococcus, and Citrobacter significantly influences the treatment duration. The presence of these microorganisms is associated with a longer treatment duration for patients. Furthermore, these microorganisms were found to impact various clinical measures. Notably, an increase in hospitalization durations and medication costs was observed in patients with these microorganisms. In patients with Colwellia, Cryptococcus, and Citrobacter, we discover significant differences in platelets levels. We also find that in patients with Cryptococcus, white blood cells, hemoglobin, and neutrophils levels are lower.

Conclusion

These findings suggest that Colwellia, Cryptococcus, and Citrobacter, particularly Cryptococcus, could potentially contribute to the severity of infections observed in this cohort, possibly as co-infections. These microorganisms warrant further investigation into their pathogenic roles and mechanisms of action, as their presence in combination with disease-causing organisms may have a synergistic effect on disease severity. Understanding the interplay between these microorganisms and pathogenic agents could provide valuable insights into the complex nature of severe pediatric infections and guide the development of targeted therapeutic strategies.

The pediatric gut bacteriome and virome in response to SARS-CoV-2 infection

Introduction

Since the beginning of the SARS-CoV-2 pandemic in early 2020, it has been apparent that children were partially protected from both infection and the more severe forms of the disease. Many different mechanisms have been proposed to explain this phenomenon, including children's frequent exposure to other upper respiratory infections and vaccines, and which inflammatory cytokines they are more likely to produce in response to infection. Furthermore, given the presence of SARS-CoV-2 in the intestine and its ability to infect enterocytes, combined with the well described immunomodulatory capabilities of the microbiome, another potential contributing factor may be the presence of certain protective microbial members of the gut microbiota (GM).

Methods

We performed shotgun metagenomic sequencing and profiled both the bacteriome and virome of the GM of pediatric SARS-CoV-2 patients compared to healthy, age-matched subjects.

Results

We found that, while pediatric patients do share some pro-inflammatory microbial signatures with adult patients, they also possess a distinct microbial signature of protective bacteria previously found to be negatively correlated with SARS-CoV-2 infectivity and COVID-19 severity. COVID-19 was also associated with higher fecal Cytomegalovirus load, and with shifts in the relative abundances of bacteriophages in the GM. Furthermore, we address how the preventative treatment of COVID-19 patients with antibiotics, a common practice especially in the early days of the pandemic, affected the bacteriome and virome, as well as the abundances of antimicrobial resistance and virulence genes in these patients.

Discussion

To our knowledge, this is the first study to address the bacteriome, virome, and resistome of pediatric patients in response to COVID-19 and to preventative antibiotics use.

Shotgun Metagenomics Reveals Minor Micro"bee"omes Diversity Defining Differences between Larvae and Pupae Brood Combs

Bees represent not only a valuable asset in agriculture, but also serve as a model organism within contemporary microbiology. The metagenomic composition of the bee superorganism has been substantially characterized. Nevertheless, traditional cultural methods served as the approach to studying brood combs in the past. Indeed, the comb microbiome may contribute to determining larval caste differentiation and hive immunity. To further this understanding, we conducted a shotgun sequencing analysis of the brood comb microbiome. While we found certain similarities regarding species diversity, it exhibits significant differentiation from all previously described hive metagenomes. Many microbiome members maintain a relatively constant ratio, yet taxa with the highest abundance level tend to be ephemeral. More than 90% of classified metagenomes were Gammaproteobacteria, Bacilli and Actinobacteria genetic signatures. Jaccard dissimilarity between samples based on bacteria genus classifications hesitate from 0.63 to 0.77, which for shotgun sequencing indicates a high consistency in bacterial composition. Concurrently, we identified antagonistic relationships between certain bacterial clusters. The presence of genes related to antibiotic synthesis and antibiotic resistance suggests potential mechanisms underlying the stability of comb microbiomes. Differences between pupal and larval combs emerge in the total metagenome, while taxa with the highest abundance remained consistent. All this suggests that a key role in the functioning of the comb microbiome is played by minor biodiversity, the function of which remains to be established experimentally.

Influence of age, socioeconomic status, and location on the infant gut resistome across populations

Antibiotic resistance is a growing global concern, with many ecological niches showing a high abundance of antibiotic resistance genes (ARGs), including the human gut. With increasing indications of ARGs in infants, this study aims to investigate the gut resistome profile during early life at a wider geographic level. To achieve this objective, we utilized stool samples data from 26 studies involving subjects aged up to 3 years from different geographical locations. The 32,277 Metagenome Assembled Genomes (MAGs) previously generated from shotgun sequencing reads from these studies were used for resistome analysis using RGI with the CARD database. This analysis showed that the distribution of ARGs across the countries in our study differed in alpha diversity and compositionally. In particular, the abundance of ARGs was found to vary by socioeconomic status and healthcare access and quality (HAQ) index. Surprisingly, countries having lower socioeconomic status and HAQ indices showed lower ARG abundance, which was contradictory to previous reports. Gram-negative genera, including Escherichia, Enterobacter, Citrobacter, and Klebsiella harbored a particularly rich set of ARGs, which included antibiotics that belong to the Reserve, Access or Watch category, such as glycopeptides, fluoroquinolones, sulfonamides, macrolides, and tetracyclines. We showed that ARG abundance exponentially decreased with time during the first 3 years of life. Many highly ARG-abundant species including Escherichia, Klebsiella, Citrobacter species that we observed are well-known pathobionts found in the infant gut in early life. High abundance of these species and a diverse range of ARGs in their genomes point toward the infant gut, acting as an ARG reservoir. This is a concern and further studies are needed to examine the causal effect and its consequences on long-term health.

Towards exhaustive community ecology via DNA metabarcoding

Exhaustive biodiversity data, covering all the taxa in an environment, would be fundamental to understand how global changes influence organisms living at different trophic levels, and to evaluate impacts on interspecific interactions. Molecular approaches such as DNA metabarcoding are boosting our ability to perform biodiversity inventories. Nevertheless, even though a few studies have recently attempted exhaustive reconstructions of communities, holistic assessments remain rare. The majority of metabarcoding studies published in the last years used just one or two markers and analysed a limited number of taxonomic groups. Here, we provide an overview of emerging approaches that can allow all-taxa biological inventories. Exhaustive biodiversity assessments can be attempted by combining a large number of specific primers, by exploiting the power of universal primers, or by combining specific and universal primers to obtain good information on key taxa while limiting the overlooked biodiversity. Multiplexes of primers, shotgun sequencing and capture enrichment may provide a better coverage of biodiversity compared to standard metabarcoding, but still require major methodological advances. Here, we identify the strengths and limitations of different approaches, and suggest new development lines that might improve broad scale biodiversity analyses in the near future. More holistic reconstructions of ecological communities can greatly increase the value of metabarcoding studies, improving understanding of the consequences of ongoing environmental changes on the multiple components of biodiversity.

Gut microbiome and blood glucose control in type 1 diabetes: a systematic review

Objective

The risk of developing micro- and macrovascular complications is higher for individuals with type 1 diabetes (T1D). Numerous studies have indicated variations in gut microbial composition between healthy individuals and those with T1D. These changes in the gut ecosystem may lead to inflammation, modifications in intestinal permeability, and alterations in metabolites. Such effects can collectively impact the metabolic regulation system, thereby influencing blood glucose control. This review aims to explore the relationship between the gut microbiome, inflammation, and blood glucose parameters in patients with T1D.

Methods

Google Scholar, PubMed, and Web of Science were systematically searched from 2003 to 2023 using the following keywords: "gut microbiota," "gut microbiome," "bacteria," "T1D," "type 1 diabetes," "autoimmune diabetes," "glycemic control," "glucose control," "HbA1c," "inflammation," "inflammatory," and "cytokine." The examination has shown 18,680 articles with relevant keywords. After the exclusion of irrelevant articles, seven observational papers showed a distinct gut microbial signature in T1D patients.

Results

This review shows that, in T1D patients, HbA1c level was negatively correlated with abundance of Prevotella, Faecalibacterium, and Ruminococcaceae and positively correlated with abundance of Dorea formicigenerans, Bacteroidetes, Lactobacillales, and Bacteriodes. Instead, Bifidobacteria was negatively correlated with fasting blood glucose. In addition, there was a positive correlation between Clostridiaceae and time in range. Furthermore, a positive correlation between inflammatory parameters and gut dysbiosis was revealed in T1D patients.

Conclusion

We draw the conclusion that the gut microbiome profiles of T1D patients and healthy controls differ. Patients with T1D may experience leaky gut, bacterial translocation, inflammation, and poor glucose management due to microbiome dysbiosis. Direct manipulation of the gut microbiome in humans and its effects on gut permeability and glycemic control, however, have not been thoroughly investigated. Future research should therefore thoroughly examine other potential pathophysiological mechanisms in larger studies.

High potential for biomass-degrading CAZymes revealed by pine forest soil metagenomics

The undisturbed environment in Netarhat, with its high levels of accumulated lignocellulosic biomass, presents an opportunity to identify microbes for biomass digestion. This study focuses on the bioprospecting of native soil microbes from the Netarhat forest in Jharkhand, India, with the potential for lignocellulosic substrate digestion. These biocatalysts could help overcome the bottleneck of biomass saccharification and reduce the overall cost of biofuel production, replacing harmful fossil fuels. The study used metagenomic analysis of pine forest soil via whole genome shotgun sequencing, revealing that most of the reads matched with the bacterial species, very low percentage of reads (0.1%) belongs to fungal species, with 13% of unclassified reads. Actinobacteria were found to be predominant among the bacterial species. MetaErg annotation identified 11,830 protein family genes and 2 metabolic marker genes in the soil samples. Based on the Carbohydrate Active EnZyme (CAZy) database, 3,996 carbohydrate enzyme families were identified, with family Glycosyl hydrolase (GH) dominating with 1,704 genes. Most observed GH families in the study were GH0, 3, 5, 6. 9, 12. 13, 15, 16, 39, 43, 57, and 97. Modelling analysis of a representative GH 43 gene suggested a strong affinity for cellulose than xylan. This study highlights the lignocellulosic digestion potential of the native microfauna of the lesser-known pine forest of Netarhat.Communicated by Ramaswamy H. Sarma.

Library preparation method and DNA source influence endogenous DNA recovery from 100-year-old avian museum specimens

Museum specimens collected prior to cryogenic tissue storage are increasingly being used as genetic resources, and though high-throughput sequencing is becoming more cost-efficient, whole genome sequencing (WGS) of historical DNA (hDNA) remains inefficient and costly due to its short fragment sizes and high loads of exogenous DNA, among other factors. It is also unclear how sequencing efficiency is influenced by DNA sources. We aimed to identify the most efficient method and DNA source for collecting WGS data from avian museum specimens. We analyzed low-coverage WGS from 60 DNA libraries prepared from four American Robin (Turdus migratorius) and four Abyssinian Thrush (Turdus abyssinicus) specimens collected in the 1920s. We compared DNA source (toepad versus incision-line skin clip) and three library preparation methods: (1) double-stranded DNA (dsDNA), single tube (KAPA); (2) single-stranded DNA (ssDNA), multi-tube (IDT); and (3) ssDNA, single tube (Claret Bioscience). We found that the ssDNA, multi-tube method resulted in significantly greater endogenous DNA content, average read length, and sequencing efficiency than the other tested methods. We also tested whether a predigestion step reduced exogenous DNA in libraries from one specimen per species and found promising results that warrant further study. The ~10% increase in average sequencing efficiency of the best-performing method over a commonly implemented dsDNA library preparation method has the potential to significantly increase WGS coverage of hDNA from bird specimens. Future work should evaluate the threshold for specimen age at which these results hold and how the combination of library preparation method and DNA source influence WGS in other taxa.

Cefquinome shows a higher impact on the pig gut microbiome and resistome compared to ceftiofur

Cephalosporins are licensed for treatment of severe bacterial infections in different species. However, the effect of these antimicrobials on the fecal microbiome and potential spread of resistance-associated genes causes great concern. This highlights the need to understand the impact of cephalosporins on the porcine fecal microbiome and resistome. A combination of long-read 16S rRNA gene and shotgun metagenomic sequencing was applied to investigate the effect of conventional treatment with either ceftiofur (3 mg.kg^-1 intramuscular, 3 consecutive days) or cefquinome (2 mg.kg^-1 intramuscular, 5 consecutive days) on the porcine microbiome and resistome. Fecal samples were collected from 17 pigs (6 ceftiofur treated, 6 cefquinome treated, 5 control pigs) at four different timepoints. Treatment with ceftiofur resulted in an increase in Proteobacteria members on microbiome level, while on resistome level selection in TetQ containing Bacteroides, CfxA6 containing Prevotella and bla_TEM-1 containing Escherichia coli was observed. Cefquinome treatment resulted in a decline in overall species richness (α-diversity) and increase in Proteobacteria members. On genus level, administration of cefquinome significantly affected more genera than ceftiofur (18 vs 8). On resistome level, cefquinome resulted in a significant increase of six antimicrobial resistance genes, with no clear correlation with certain genera. For both antimicrobials, the resistome levels returned back to the control levels 21 days post-treatment. Overall, our study provides novel insights on the effect of specific cephalosporins on the porcine gut microbiome and resistome after conventional intramuscular treatment. These results might contribute to better tailoring of the most ideal treatment strategy for some bacterial infections.

Shotgun sequencing of sonication fluid for the diagnosis of orthopaedic implant-associated infections with Cutibacterium acnes as suspected causative agent

Orthopaedic implant-associated infections (OIAIs) due to Cutibacterium acnes can be difficult to diagnose. The aim of this pilot study was to determine if metagenomic next-generation sequencing (mNGS) can provide additional information to improve the diagnosis of C. acnes OIAIs. mNGS was performed on sonication fluid (SF) specimens derived from 24 implants. These were divided into three groups, based on culture results: group I, culture-negative (n = 4); group II, culture-positive for C. acnes (n = 10); and group III, culture-positive for other bacteria (n = 10). In group I, sequence reads from C. acnes were detected in only one SF sample, originating from a suspected case of OIAIs, which was SF and tissue culture-negative. In group II, C. acnes sequences were detected in 7/10 samples. In group III, C. acnes sequence reads were found in 5/10 samples, in addition to sequence reads that matched the bacterial species identified by culture. These samples could represent polymicrobial infections that were missed by culture. Taken together, mNGS was able to detect C. acnes DNA in more samples compared to culture and could be used to identify cases of suspected C. acnes OIAIs, in particular regarding possible polymicrobial infections, where the growth of C. acnes might be compromised due to a fast-growing bacterial species. However, since SF specimens are usually low-biomass samples, mNGS is prone to DNA contamination, possibly introduced during DNA extraction or sequencing procedures. Thus, it is advisable to set a sequence read count threshold, taking into account project- and NGS-specific criteria.

Bacterial gut microbiome differences in adults with ADHD and in children with ADHD on psychostimulant medication

Recent evidence suggests that there is a link between neurodevelopmental disorders, such as attention deficit hyperactivity disorder (ADHD), and the gut microbiome. However, most studies to date have had low sample sizes, have not investigated the impact of psychostimulant medication, and have not adjusted for potential confounders, including body mass index, stool consistency and diet. To this end, we conducted the largest, to our knowledge, fecal shotgun metagenomic sequencing study in ADHD, with 147 well-characterized adult and child patients. For a subset of individuals, plasma levels of inflammatory markers and short-chain fatty acids were also measured. In adult ADHD patients (n=84), compared to controls (n=52), we found a significant difference in beta diversity both regarding bacterial strains (taxonomic) and bacterial genes (functional). In children with ADHD (n=63), we found that those on psychostimulant medication (n=33 on medication vs. n=30 not on medication) had (i) significantly different taxonomic beta diversity, (ii) lower functional and taxonomic evenness, (iii) lower abundance of the strain Bacteroides stercoris CL09T03C01 and bacterial genes encoding an enzyme in vitamin B₁₂ synthesis, and (iv) higher plasma levels of vascular inflammatory markers sICAM-1 and sVCAM-1. Our study continues to support a role for the gut microbiome in neurodevelopmental disorders and provides additional insights into the effects of psychostimulant medication. However, additional studies are needed to replicate these findings and examine causal relationships with the disorder.

Metagenomes from Coastal Sediments of Kuwait: Insights into the Microbiome, Metabolic Functions and Resistome

Coastal sediments in the proximity of wastewater and emergency outfalls are often sinks of pharmaceutical compounds and other organic and inorganic contaminants that are likely to affect the microbial community. The metabolites of these contaminants affect microbial diversity and their metabolic processes, resulting in undesirable effects on ecosystem functioning, thus necessitating the need to understand their composition and functions. In the present investigation, we studied the metagenomes of 12 coastal surface sediments through whole genome shot-gun sequencing. Taxonomic binning of the genes predicted about 86% as bacteria, 1% as archaea, >0.001% as viruses and Eukaryota, and 12% as other communities. The dominant bacterial, archaeal, and fungal genera were Woeseia, Nitrosopumilus, and Rhizophagus, respectively. The most prevalent viral families were Myoviridae and Siphoviridae, and the T4 virus was the most dominant bacteriophage. The unigenes further aligned to 26 clusters of orthologous genes (COGs) and five carbohydrate-active enzymes (CAZy) classes. Glycoside hydrolases (GH) and glycoside transferase (GT) were the highest-recorded CAzymes. The Kyoto Encyclopedia of Genes and Genomes (KEGG) level 3 functions were subjugated by purine metabolism > ABC transporters > oxidative phosphorylation > two-component system > pyrimidine metabolism > pyruvate metabolism > quorum sensing > carbon fixation pathways > ribosomes > and glyoxalate and dicarboxylate metabolism. Sequences allying with plasmids, integrons, insertion sequences and antibiotic-resistance genes were also observed. Both the taxonomies and functional abundances exhibited variation in relative abundances, with limited spatial variability (ANOVA p > 0.05; ANOSIM-0.05, p > 0.05). This study underlines the dominant microbial communities and functional genes in the marine sediments of Kuwait as a baseline for future biomonitoring programs.

Characterization of Non-Obstructive Azoospermia in Men Using Gut Microbial Profiling

(1) Background: Non-obstructive azoospermia (NOA) is a complex multifactorial disease and the causes of most NOA cases remain unknown. (2) Methods: Here, we performed comprehensive clinical analyses and gut microbial profiling using shotgun metagenomic sequencing in patients with NOA and control individuals. (3) Results: The gut microbial alpha and beta diversity significantly differed between patients with NOA and controls. Several microbial strains, including Bacteroides vulgatus and Streptococcus thermophilus, were significantly more abundant in the NOA group, whereas Bacteroides thetaiotaomicron and Parabacteroides sp. CT06 were enriched in the control group. Moreover, functional pathway analysis suggested that the altered microbiota in NOA suppressed the carbohydrate metabolism pathway, while amino acid metabolism and methane metabolism pathways were enhanced. We observed that the differential microbial species, such as Acinetobacter johnsonii, had a strong correlation with clinical parameters, including age, body mass index, testosterone, and follicle-stimulating hormone. Communication and interplay among microbial genera were significantly increased in NOA than in the control group. (4) Conclusions: Altered microbial composition and functional pathways in the NOA group were revealed, which highlight the utility of gut microbiota in understanding microbiota-related pathogenesis of NOA and might be helpful to the clinical management of NOA.

Decoding the microbial universe with metagenomics: a brief insight

A major part of any biological system on earth involves microorganisms, of which the majority are yet to be cultured. The conventional methods of culturing microbes have given fruitful outcomes yet have limitations. The curiosity for better understanding has led to the development of culture-independent molecular methods that help push aside the roadblocks of earlier methods. Metagenomics unifies the scientific community in search of a better understanding of the functioning of the ecosystem and its component organisms. This approach has opened a new paradigm in advanced research. It has brought to light the vast diversity and novelty among microbial communities and their genomes. This review focuses on the development of this field over time, the techniques and analysis of data generated through sequencing platforms, and its prominent interpretation and representation.

Comparison of Metagenomics and Metatranscriptomics Tools: A Guide to Making the Right Choice

The study of microorganisms is a field of great interest due to their environmental (e.g., soil contamination) and biomedical (e.g., parasitic diseases, autism) importance. The advent of revolutionary next-generation sequencing techniques, and their application to the hypervariable regions of the 16S, 18S or 23S ribosomal subunits, have allowed the research of a large variety of organisms more in-depth, including bacteria, archaea, eukaryotes and fungi. Additionally, together with the development of analysis software, the creation of specific databases (e.g., SILVA or RDP) has boosted the enormous growth of these studies. As the cost of sequencing per sample has continuously decreased, new protocols have also emerged, such as shotgun sequencing, which allows the profiling of all taxonomic domains in a sample. The sequencing of hypervariable regions and shotgun sequencing are technologies that enable the taxonomic classification of microorganisms from the DNA present in microbial communities. However, they are not capable of measuring what is actively expressed. Conversely, we advocate that metatranscriptomics is a "new" technology that makes the identification of the mRNAs of a microbial community possible, quantifying gene expression levels and active biological pathways. Furthermore, it can be also used to characterise symbiotic interactions between the host and its microbiome. In this manuscript, we examine the three technologies above, and discuss the implementation of different software and databases, which greatly impact the obtaining of reliable results. Finally, we have developed two easy-to-use pipelines leveraging Nextflow technology. These aim to provide everything required for an average user to perform a metagenomic analysis of marker genes with QIMME2 and a metatranscriptomic study using Kraken2/Bracken.

Gut Microbiome Studies in Livestock: Achievements, Challenges, and Perspectives

The variety and makeup of the gut microbiome are frequently regarded as the primary determinants of health and production performances in domestic animals. High-throughput DNA/RNA sequencing techniques (NGS) have recently gained popularity and permitted previously unheard-of advancements in the study of gut microbiota, particularly for determining the taxonomic composition of such complex communities. Here, we summarize the existing body of knowledge on livestock gut microbiome, discuss the state-of-the-art in sequencing techniques, and offer predictions for next research. We found that the enormous volumes of available data are biased toward a small number of globally distributed and carefully chosen varieties, while local breeds (or populations) are frequently overlooked despite their demonstrated resistance to harsh environmental circumstances. Furthermore, the bulk of this research has mostly focused on bacteria, whereas other microbial components such as protists, fungi, and viruses have received far less attention. The majority of these data were gathered utilizing traditional metabarcoding techniques that taxonomically identify the gut microbiota by analyzing small portions of their genome (less than 1000 base pairs). However, to extend the coverage of microbial genomes for a more precise and thorough characterization of microbial communities, a variety of increasingly practical and economical shotgun techniques are currently available.

Healthcare Derived Smart Watches and Mobile Phones are Contaminated Niches to Multidrug Resistant and Highly Virulent Microbes

Background

As high touch wearable devices, the potential for microbial contamination of smart watches is high. In this study, microbial contamination of smart watches of healthcare workers (HCWs) was assessed and compared to the individual’s mobile phone and hands.

Methods

This study was part of a larger point prevalence survey of microbial contamination of mobile phones of HCWs at the emergency unit of a tertiary care facility. Swabs from smart watches, mobile phones and hands were obtained from four HCWs with dual ownership of these digital devices. Bacterial culture was carried out for all samples and those from smart watches and mobile phones were further assessed using shotgun metagenomic sequencing.

Results

Majority of the participants were females (n/N = 3/4; 75%). Although they all use their digital devices at work and believe that these devices could harbour microbes, cleaning in the preceding 24 hours was reported by one individual. Predominant organisms identified on bacterial culture were multidrug resistant Staphylococcus hominis and Staphylococcus epidermidis. At least one organism identified from the hands was also detected on all mobile phones and two smart watches. Shotgun metagenomics analysis demonstrated greater microbial number and diversity on mobile phones compared to smart watches. All devices had high signatures of Pseudomonas aeruginosa and associated bacteriophages and antibiotic resistance genes. Almost half of the antibiotic resistance genes (n/N = 35/75;46.6%) were present on all devices and majority were related to efflux pumps. Of the 201 virulence factor genes (VFG) identified, majority (n/N = 148/201;73%) were associated with P. aeruginosa with 96% (n/N = 142/148) present on smart watches and mobile phones.

Conclusion

This first report on microbial contamination of smart watches using metagenomics next generation sequencing showed similar pattern of contamination with microbes, VFG and antibiotic resistance genes across digital devices. Further studies on microbial contamination of wearable digital devices are urgently needed.

Statistical challenges in longitudinal microbiome data analysis

The microbiome is a complex and dynamic community of microorganisms that co-exist interdependently within an ecosystem, and interact with its host or environment. Longitudinal studies can capture temporal variation within the microbiome to gain mechanistic insights into microbial systems; however, current statistical methods are limited due to the complex and inherent features of the data. We have identified three analytical objectives in longitudinal microbial studies: (1) differential abundance over time and between sample groups, demographic factors or clinical variables of interest; (2) clustering of microorganisms evolving concomitantly across time and (3) network modelling to identify temporal relationships between microorganisms. This review explores the strengths and limitations of current methods to fulfill these objectives, compares different methods in simulation and case studies for objectives (1) and (2), and highlights opportunities for further methodological developments. R tutorials are provided to reproduce the analyses conducted in this review.

Microbiome Analysis for Wastewater Surveillance during COVID-19

Wastewater surveillance (WS), when coupled with advanced molecular techniques, offers near real-time monitoring of community-wide transmission of SARS-CoV-2 and allows assessing and mitigating COVID-19 outbreaks, by evaluating the total microbial assemblage in a community. Composite wastewater samples (24 h) were collected weekly from a manhole between December 2020 and November 2021 in Maryland, USA. RT-qPCR results showed concentrations of SARS-CoV-2 RNA recovered from wastewater samples reflected incidence of COVID-19 cases. When a drastic increase in COVID-19 was detected in February 2021, samples were selected for microbiome analysis (DNA metagenomics, RNA metatranscriptomics, and targeted SARS-CoV-2 sequencing). Targeted SARS-CoV-2 sequencing allowed for detection of important genetic mutations, such as spike: K417N, D614G, P681H, T716I, S982A, and D1118H, commonly associated with increased cell entry and reinfection. Microbiome analysis (DNA and RNA) provided important insight with respect to human health-related factors, including detection of pathogens and their virulence/antibiotic resistance genes. Specific microbial species comprising the wastewater microbiome correlated with incidence of SARS-CoV-2 RNA, suggesting potential association with SARS-CoV-2 infection. Climatic conditions, namely, temperature, were related to incidence of COVID-19 and detection of SARS-CoV-2 in wastewater, having been monitored as part of an environmental risk score assessment carried out in this study. In summary, the wastewater microbiome provides useful public health information, and hence, a valuable tool to proactively detect and characterize pathogenic agents circulating in a community. In effect, metagenomics of wastewater can serve as an early warning system for communicable diseases, by providing a larger source of information for health departments and public officials. IMPORTANCE Traditionally, testing for COVID-19 is done by detecting SARS-CoV-2 in samples collected from nasal swabs and/or saliva. However, SARS-CoV-2 can also be detected in feces of infected individuals. Therefore, wastewater samples can be used to test all individuals of a community contributing to the sewage collection system, i.e., the infrastructure, such as gravity pipes, manholes, tanks, lift stations, control structures, and force mains, that collects used water from residential and commercial sources and conveys the flow to a wastewater treatment plant. Here, we profile community wastewater collected from a manhole, detect presence of SARS-CoV-2, identify genetic mutations of SARS-CoV-2, and perform COVID-19 risk score assessment of the study area. Using metagenomics analysis, we also detect other microorganisms (bacteria, fungi, protists, and viruses) present in the samples. Results show that by analyzing all microorganisms present in wastewater, pathogens circulating in a community can provide an early warning for contagious diseases.

Effects of Dietary Antimicrobial Growth Promoters on Performance Parameters and Abundance and Diversity of Broiler Chicken Gut Microbiome and Selection of Antibiotic Resistance Genes

Antimicrobial growth promoters (AGPs) are commonly used in broiler production. There is a huge societal concern around their use and their contribution to the proliferation of antimicrobial resistance (AMR) in food-producing animals and dissemination to humans or the environment. However, there is a paucity of comprehensive experimental data on their impact on poultry production and the AMR resistome. Here, we investigated the effect of five antimicrobial growth promoters (virginiamycin, chlortetracycline, bacitracin methyl disalicylate, lincomycin, and tylosin) used in the commercial broiler production in the Indian subcontinent and in the different parts of the world for three consecutive production cycles on performance variables and also the impact on gut bacteria, bacteriophage, and resistome profile using culture-independent approaches. There was no significant effect of AGPs on the cumulative growth or feed efficiency parameters at the end of the production cycles and cumulative mortality rates were also similar across groups. Many antibiotic resistance genes (ARGs) were ubiquitous in the chicken gut irrespective of AGP supplementation. In total, 62 ARGs from 15 antimicrobial classes were detected. Supplementation of AGPs influenced the selection of several classes of ARGs; however, this was not correlated necessarily with genes relevant to the AGP drug class; some AGPs favored the selection of ARGs related to antimicrobials not structurally related to the AGP. AGPs did not impact the gut bacterial community structure, including alpha or beta diversity significantly, with only 16-20 operational taxonomic units (OTUs) of bacteria being altered significantly. However, several AGPs significantly reduced the population density of some of the potential pathogenic genera of bacteria, such as Escherichia coli. Chlortetracycline increased the abundance of Escherichia phage, whereas other AGPs did not influence the abundance of bacteriophage significantly. Considering the evidence that AGPs used in poultry production can select for resistance to more than one class of antimicrobial resistance, and the fact that their effect on performance is not significant, their use needs to be reduced and there is a need to monitor the spread of ARGs in broiler chicken farms.

Detection of E. coli IncX1 Plasmid-Mediated mcr-5.1 Gene in an Indian Hospital Sewage Water Using Shotgun Metagenomic Sequencing: A First Report

Colistin is used against a multitude of multidrug-resistant and extremely drug-resistant Gram-negative bacterial infections. The emergence of colistin resistance is highly concerning as it may lead to the failure of this last-resort antibiotic. Since the identification of first mobile colistin resistance (mcr) genes, several variants of mcr genes have been reported, but still there are limited studies detecting mcr genes in hospital sewage water. The prevalence of mcr in the hospital environment is extremely hazardous putting health care workers, patients, and visitors at a higher risk of exposure. It may lead to a multidrug-resistant bacterial infection outbreak. In this study, we report mcr-5.1 gene in an Indian hospital sewage water using shotgun metagenomics, as a first report. The mcr-5.1 gene in the metagenome has been explored using RGI, ABRicate, NCBI database, CARD, and Resfinder. This mcr-5.1 gene harbored by Escherichia coli is a plasmid-mediated gene carried by an IncX1 plasmid pSGMCR103. The bioinformatics analysis revealed the genetic environment of mcr-5.1 gene, which consisted of mobile element protein, ChrB domain protein, putative major facilitator superfamily type transporter, and a hypothetical protein.

Bee foraging preferences, microbiota and pathogens revealed by direct shotgun metagenomics of honey

Honeybees (Apis mellifera) continue to succumb to human and environmental pressures despite their crucial role in providing essential ecosystem services. Owing to their foraging and honey production activities, honeybees form complex relationships with species across all domains, such as plants, viruses, bacteria and other hive pests, making honey a valuable biomonitoring tool for assessing their ecological niche. Thus, the application of honey shotgun metagenomics (SM) has paved the way for a detailed description of the species honeybees interact with. Nevertheless, SM bioinformatics tools and DNA extraction methods rely on resources not necessarily optimized for honey. In this study, we compared five widely used taxonomic classifiers using simulated species communities commonly found in honey. We found that Kraken 2 with a threshold of 0.5 performs best in assessing species distribution. We also optimized a simple NaOH-based honey DNA extraction methodology (Direct-SM), which profiled species seasonal variability similarly to an established column-based DNA extraction approach (SM). Both approaches produce results consistent with melissopalinology analysis describing the botanical landscape surrounding the apiary. Interestingly, we detected a strong stability of the bacteria constituting the core and noncore gut microbiome across seasons, pointing to the potential utility of honey for noninvasive assessment of bee microbiota. Finally, the Direct-SM approach to detect Varroa correlates well with the biomonitoring of mite infestation observed in hives. These observations suggest that Direct-SM methodology has the potential to comprehensively describe honeybee ecological niches and can be tested as a building block for large-scale studies to assess bee health in the field.

Emergent marine toxins risk assessment using molecular and chemical approaches

Cyanobacteria harmful blooms represent a deviation to the normal equilibrium in planktonic communities involving a rapid and uncontrolled growth. Owing to the capacity to produce toxins as secondary metabolites, cyanobacteria may cause huge economic losses in the fishing and aquaculture industries and poisoning incidents to humans due to their accumulation in the food chain. The conditions which promote toxic blooms have not yet been fully understood, but climate change and anthropogenic intervention are pointed as significant factors. For the detection of toxins in edible marine organisms, the establishment of international regulations and compulsory surveillance has been probed as exceptionally effective. However, not regulation nor monitoring have been settled concerning emergent marine toxins. In the light of this scenario, it becomes essential to apply fast and reliable surveillance methodologies for the early detection of cyanobacterial blooms as well as the occurrence of emergent marine toxins. Shotgun metagenomic sequencing has potential to become a powerful diagnostic tool in the fields of food safety and One Health surveillance. This culture‐independent approach overcomes limitations of traditional microbiological techniques; it allows a quick and accurate assessment of a complex microbial community, including quantitative identification and functional characterisation, in a single experiment. In the framework of the EU‐FORA fellowship, with the final goal of evaluate metagenomics as a promising risk assessment tool, the fellow worked on the development of an innovative workflow through state‐of‐the‐art molecular and chemical analytical procedures. This work programme aims to evaluate the occurrence of emergent marine toxins and the producing organisms in Cabo Verde coastal cyanobacteria blooms. Our results show the outstanding potential of a holistic metagenomic approach for the risk assessment of emergent marine toxins and the producing organisms. Additionally, we have also highlighted its value for the identification and evaluation of secondary metabolites as natural bioactive compounds with biotechnological and industrial interest.

Computational analyses of bacterial strains from shotgun reads

Shotgun sequencing is routinely employed to study bacteria in microbial communities. With the vast amount of shotgun sequencing reads generated in a metagenomic project, it is crucial to determine the microbial composition at the strain level. This study investigated 20 computational tools that attempt to infer bacterial strain genomes from shotgun reads. For the first time, we discussed the methodology behind these tools. We also systematically evaluated six novel-strain-targeting tools on the same datasets and found that BHap, mixtureS and StrainFinder performed better than other tools. Because the performance of the best tools is still suboptimal, we discussed future directions that may address the limitations.

Advances in Metagenomics and Its Application in Environmental Microorganisms

Metagenomics is a new approach to study microorganisms obtained from a specific environment by functional gene screening or sequencing analysis. Metagenomics studies focus on microbial diversity, community constitute, genetic and evolutionary relationships, functional activities, and interactions and relationships with the environment. Sequencing technologies have evolved from shotgun sequencing to high-throughput, next-generation sequencing (NGS), and third-generation sequencing (TGS). NGS and TGS have shown the advantage of rapid detection of pathogenic microorganisms. With the help of new algorithms, we can better perform the taxonomic profiling and gene prediction of microbial species. Functional metagenomics is helpful to screen new bioactive substances and new functional genes from microorganisms and microbial metabolites. In this article, basic steps, classification, and applications of metagenomics are reviewed.

A pilot study of microbial signatures of liver disease in those with HIV mono-infection in Rio de Janeiro, Brazil

OBJECTIVE

The rectal microbiome was examined to assess the relationship between the microbiome and liver disease in HIV-infection.

DESIGN

Eighty-two HIV-1 mono-infected individuals from the PROSPEC-HIV-study (NCT02542020) were grouped into three liver health categories based on results of controlled attenuation parameter (CAP) and liver stiffness measurement (LSM) of transient elastography: normal (n = 30), steatosis (n = 30), or fibrosis (n = 22).

METHODS

Liver steatosis and fibrosis were defined by CAP at least 248 dB/m and LSM at least 8.0 kPa, respectively. 16S rRNA gene and whole genome shotgun metagenomic sequencing were performed on rectal swabs. Bacterial differences were assessed using zero-inflated negative binomial regression and random forests modeling; taxonomic drivers of functional shifts were identified using FishTaco.

RESULTS

Liver health status explained four percentage of the overall variation (r2 = 0.04, P = 0.003) in bacterial composition. Participants with steatosis had depletions of Akkermansia muciniphila and Bacteroides dorei and enrichment of Prevotella copri, Finegoldia magna, and Ruminococcus bromii. Participants with fibrosis had depletions of Bacteroides stercoris and Parabacteroides distasonis and enrichment of Sneathia sanguinegens. In steatosis, functional analysis revealed increases in primary and secondary bile acid synthesis encoded by increased Eubacterium rectale, F. magna, and Faecalibacterium prausnitzii and decreased A. muciniphila, Bacteroides fragilis and B. dorei. Decreased folate biosynthesis was driven by similar changes in microbial composition.

CONCLUSION

HIV mono-infection with steatosis or fibrosis had distinct microbial profiles. Some taxa are similar to those associated with non-alcoholic fatty liver disease in HIV-negative populations. Further studies are needed to define the role of the gut microbiota in the pathogenesis of liver disease in HIV-infected persons.

Mycobacterium chelonae Infection Identified by Metagenomic Next-Generation Sequencing as the Probable Cause of Acute Contained Rupture of a Biological Composite Graft-A Case Report

We present the case of a 72-year-old female patient with acute contained rupture of a biological composite graft, 21 months after replacement of the aortic valve and the ascending aorta due to an aortic dissection. Auramine-rhodamine staining of intraoperative biopsies showed acid-fast bacilli, but classical culture and molecular methods failed to identify any organism. Metagenomic analysis indicated infection with Mycobacterium chelonae, which was confirmed by target-specific qPCR. The complexity of the sample required a customized bioinformatics pipeline, including cleaning steps to remove sequences of human, bovine ad pig origin. Our study underlines the importance of multiple testing to increase the likelihood of pathogen identification in highly complex samples.

Whole-genome sequencing reveals forgotten lineages and recurrent hybridizations within the kelp genus Alaria (Phaeophyceae)

The genomic era continues to revolutionize our understanding of the evolution of biodiversity. In phycology, emphasis remains on assembling nuclear and organellar genomes, leaving the full potential of genomic datasets to answer long-standing questions about the evolution of biodiversity largely unexplored. Here, we used whole-genome sequencing (WGS) datasets to survey species diversity in the kelp genus Alaria, compare phylogenetic signals across organellar and nuclear genomes, and specifically test whether phylogenies behave like trees or networks. Genomes were sequenced from across the global distribution of Alaria (including Alaria crassifolia, A. praelonga, A. crispa, A. marginata, and A. esculenta), representing over 550 GB of data and over 2.2 billion paired reads. Genomic datasets retrieved 3,814 and 4,536 single-nucleotide polymorphisms (SNPs) for mitochondrial and chloroplast genomes, respectively, and upwards of 148,542 high-quality nuclear SNPs. WGS revealed an Arctic lineage of Alaria, which we hypothesize represents the synonymized taxon A. grandifolia. The SNP datasets also revealed inconsistent topologies across genomic compartments, and hybridization (i.e., phylogenetic networks) between Pacific A. praelonga, A. crispa, and putative A. grandifolia, and between some lineages of the A. marginata complex. Our analysis demonstrates the potential for WGS data to advance our understanding of evolution and biodiversity beyond amplicon sequencing, and that hybridization is potentially an important mechanism contributing to novel lineages within Alaria. We also emphasize the importance of surveying phylogenetic signals across organellar and nuclear genomes, such that models of mixed ancestry become integrated into our evolutionary and taxonomic understanding.

[Shotgun metagenome sequencing of Chinese gut microbiota: a review]

The research on the relationship between gut microbiota and human health continues to be a hot topic in the field of life science. Culture independent 16S rRNA gene high-throughput sequencing is the current main research method. However, with the reduction of sequencing cost and the maturity of data analysis methods, shotgun metagenome sequencing is gradually becoming an important method for the study of gut microbiome due to its advantages of obtaining more information. With the support from the human microbiome project, 30 805 metagenome samples were sequenced in the United States. By searching NCBI PubMed and SRA databases, it was found that 72 studies collecting about 10 000 Chinese intestinal samples were used for metagenome sequencing. To date, only 56 studies were published, including 16 related to metabolic diseases, 16 related to infectious and immune diseases, and 12 related to cardiovascular and cerebrovascular diseases. The samples were mainly collected in Beijing, Guangzhou, Shanghai and other cosmopolitan cities, where great differences exist in sequencing platforms and methods. The outcome of most studies are based on correlation analysis, which has little practical value in guiding the diagnosis and treatment of clinical diseases. Standardizing sampling methods, sequencing platform and data analysis process, and carrying out multi center parallel research will contribute to data integration and comparative analysis. Moreover, insights into the functional verification and molecular mechanism by using the combination of transcriptomics, proteomics and culturomics will enable the gut microbiota research to better serve the clinical diagnosis and treatment.

Surveillance of Listeria monocytogenes: Early Detection, Population Dynamics, and Quasimetagenomic Sequencing during Selective Enrichment

In this study, we addressed different aspects regarding the implementation of quasimetagenomic sequencing as a hybrid surveillance method in combination with enrichment for early detection of Listeria monocytogenes in the food industry. Different experimental enrichment cultures were used, comprising seven L. monocytogenes strains of different sequence types (STs), with and without a background microbiota community. To assess whether the proportions of the different STs changed over time during enrichment, the growth and population dynamics were assessed using dapE colony sequencing and dapE and 16S rRNA amplicon sequencing. There was a tendency of some STs to have a higher relative abundance during the late stage of enrichment when L. monocytogenes was enriched without background microbiota. When coenriched with background microbiota, the population dynamics of the different STs was more consistent over time. To evaluate the earliest possible time point during enrichment that allows the detection of L. monocytogenes and at the same time the generation of genetic information that enables an estimation regarding the strain diversity in a sample, quasimetagenomic sequencing was performed early during enrichment in the presence of the background microbiota using Oxford Nanopore Technologies Flongle and Illumina MiSeq sequencing. The application of multiple displacement amplification (MDA) enabled detection of L. monocytogenes (and the background microbiota) after only 4 h of enrichment using both applied sequencing approaches. The MiSeq sequencing data additionally enabled the prediction of cooccurring L. monocytogenes strains in the samples.

IMPORTANCE We showed that a combination of a short primary enrichment combined with MDA and Nanopore sequencing can accelerate the traditional process of cultivation and identification of L. monocytogenes. The use of Illumina MiSeq sequencing additionally allowed us to predict the presence of cooccurring L. monocytogenes strains. Our results suggest quasimetagenomic sequencing is a valuable and promising hybrid surveillance tool for the food industry that enables faster identification of L. monocytogenes during early enrichment. Routine application of this approach could lead to more efficient and proactive actions in the food industry that prevent contamination and subsequent product recalls and food destruction, economic and reputational losses, and human listeriosis cases.

Linking Inflammatory Bowel Disease Symptoms to Changes in the Gut Microbiome Structure and Function

Inflammatory bowel disease (IBD) is a chronic disease of the gastrointestinal tract that is often characterized by abdominal pain, rectal bleeding, inflammation, and weight loss. Many studies have posited that the gut microbiome may play an integral role in the onset and exacerbation of IBD. Here, we present a novel computational analysis of a previously published IBD dataset. This dataset consists of shotgun sequence data generated from fecal samples collected from individuals with IBD and an internal control group. Utilizing multiple external controls, together with appropriate techniques to handle the compositionality aspect of sequence data, our computational framework can identify and corroborate differences in the taxonomic profiles, bacterial association networks, and functional capacity within the IBD gut microbiome. Our analysis identified 42 bacterial species that are differentially abundant between IBD and every control group (one internal control and two external controls) with at least a twofold difference. Of the 42 species, 34 were significantly elevated in IBD, relative to every other control. These 34 species were still present in the control groups and appear to play important roles, according to network centrality and degree, in all bacterial association networks. Many of the species elevated in IBD have been implicated in modulating the immune response, mucin degradation, antibiotic resistance, and inflammation. We also identified elevated relative abundances of protein families related to signal transduction, sporulation and germination, and polysaccharide degradation as well as decreased relative abundance of protein families related to menaquinone and ubiquinone biosynthesis. Finally, we identified differences in functional capacities between IBD and healthy controls, and subsequently linked the changes in the functional capacity to previously published clinical research and to symptoms that commonly occur in IBD.

Two-Target Quantitative PCR To Predict Library Composition for Shallow Shotgun Sequencing

When determining human microbiota composition, shotgun sequencing is a powerful tool that can generate high-resolution taxonomic and functional information at once. However, the technique is limited by missing information about host-to-microbe ratios observed in different body compartments. This limitation makes it difficult to plan shotgun sequencing assays, especially in the context of high sample multiplexing and limited sequencing output and is of particular importance for studies employing the recently described shallow shotgun sequencing technique. In this study, we evaluated the use of a quantitative PCR (qPCR)-based assay to predict host-to-microbe ratio prior to sequencing. Combining a two-target assay involving the bacterial 16S rRNA gene and the human beta-actin gene, we derived a model to predict human-to-microbe ratios from two sample types, including stool samples and oropharyngeal swabs. We then validated it on two independently collected sample types, including rectal swabs and vaginal secretion samples. This assay enabled accurate prediction in the validation set in a range of sample compositions between 4% and 98% nonhuman reads and observed proportions varied between −18.8% and +19.2% from the expected values. We hope that this easy-to-use assay will help researchers to plan their shotgun sequencing experiments in a more efficient way.

IMPORTANCE When determining human microbiota composition, shotgun sequencing is a powerful tool that can generate large amounts of data. However, in sample compositions with low or variable microbial density, shallowing sequencing can negatively affect microbial community metrics. Here, we show that variable sequencing depth decreases measured alpha diversity at differing rates based on community composition. We then derived a model that can determine sample composition prior to sequencing using quantitative PCR (qPCR) data and validated the model using a separate sample set. We have included a tool that uses this model to be available for researchers to use when gauging shallow sequencing viability of samples.

A global metagenomic map of urban microbiomes and antimicrobial resistance

We present a global atlas of 4,728 metagenomic samples from mass-transit systems in 60 cities over 3 years, representing the first systematic, worldwide catalog of the urban microbial ecosystem. This atlas provides an annotated, geospatial profile of microbial strains, functional characteristics, antimicrobial resistance (AMR) markers, and genetic elements, including 10,928 viruses, 1,302 bacteria, 2 archaea, and 838,532 CRISPR arrays not found in reference databases. We identified 4,246 known species of urban microorganisms and a consistent set of 31 species found in 97% of samples that were distinct from human commensal organisms. Profiles of AMR genes varied widely in type and density across cities. Cities showed distinct microbial taxonomic signatures that were driven by climate and geographic differences. These results constitute a high-resolution global metagenomic atlas that enables discovery of organisms and genes, highlights potential public health and forensic applications, and provides a culture-independent view of AMR burden in cities.

Evaluation of Metagenomic-Enabled Antibiotic Resistance Surveillance at a Conventional Wastewater Treatment Plant

Wastewater treatment plants (WWTPs) receive a confluence of sewage containing antimicrobials, antibiotic resistant bacteria, antibiotic resistance genes (ARGs), and pathogens and thus are a key point of interest for antibiotic resistance surveillance. WWTP monitoring has the potential to inform with respect to the antibiotic resistance status of the community served as well as the potential for ARGs to escape treatment. However, there is lack of agreement regarding suitable sampling frequencies and monitoring targets to facilitate comparison within and among individual WWTPs. The objective of this study was to comprehensively evaluate patterns in metagenomic-derived indicators of antibiotic resistance through various stages of treatment at a conventional WWTP for the purpose of informing local monitoring approaches that are also informative for global comparison. Relative abundance of total ARGs decreased by ∼50% from the influent to the effluent, with each sampling location defined by a unique resistome (i.e., total ARG) composition. However, 90% of the ARGs found in the effluent were also detected in the influent, while the effluent ARG-pathogen taxonomic linkage patterns identified in assembled metagenomes were more similar to patterns in regional clinical surveillance data than the patterns identified in the influent. Analysis of core and discriminatory resistomes and general ARG trends across the eight sampling events (i.e., tendency to be removed, increase, decrease, or be found in the effluent only), along with quantification of ARGs of clinical concern, aided in identifying candidate ARGs for surveillance. Relative resistome risk characterization further provided a comprehensive metric for predicting the relative mobility of ARGs and likelihood of being carried in pathogens and can help to prioritize where to focus future monitoring and mitigation. Most antibiotics that were subject to regional resistance testing were also found in the WWTP, with the total antibiotic load decreasing by ∼40–50%, but no strong correlations were found between antibiotics and corresponding ARGs. Overall, this study provides insight into how metagenomic data can be collected and analyzed for surveillance of antibiotic resistance at WWTPs, suggesting that effluent is a beneficial monitoring point with relevance both to the local clinical condition and for assessing efficacy of wastewater treatment in reducing risk of disseminating antibiotic resistance.

Metagenomics: A viable tool for reconstructing herbivore diet

Metagenomics can generate data on the diet of herbivores, without the need for primer selection and PCR enrichment steps as is necessary in metabarcoding. Metagenomic approaches to diet analysis have remained relatively unexplored, requiring validation of bioinformatic steps. Currently, no metagenomic herbivore diet studies have utilized both chloroplast and nuclear markers as reference sequences for plant identification, which would increase the number of reads that could be taxonomically informative. Here, we explore how in silico simulation of metagenomic data sets resembling sequences obtained from faecal samples can be used to validate taxonomic assignment. Using a known list of sequences to create simulated data sets, we derived reliable identification parameters for taxonomic assignments of sequences. We applied these parameters to characterize the diet of western capercaillies (Tetrao urogallus) located in Norway, and compared the results with metabarcoding trnL P6 loop data generated from the same samples. Both methods performed similarly in the number of plant taxa identified (metagenomics 42 taxa, metabarcoding 43 taxa), with no significant difference in species resolution (metagenomics 24%, metabarcoding 23%). We further observed that while metagenomics was strongly affected by the age of faecal samples, with fresh samples outperforming old samples, metabarcoding was not affected by sample age. On the other hand, metagenomics allowed us to simultaneously obtain the mitochondrial genome of the western capercaillies, thereby providing additional ecological information. Our study demonstrates the potential of utilizing metagenomics for diet reconstruction but also highlights key considerations as compared to metabarcoding for future utilization of this technique.

A Benchmark of Genetic Variant Calling Pipelines Using Metagenomic Short-Read Sequencing

Microbes live in complex communities that are of major importance for environmental ecology, public health, and animal physiology and pathology. Short-read metagenomic shotgun sequencing is currently the state-of-the-art technique for exploring these communities. With the aid of metagenomics, our understanding of the microbiome is moving from composition toward functionality, even down to the genetic variant level. While the exploration of single-nucleotide variation in a genome is a standard procedure in genomics, and many sophisticated tools exist to perform this task, identification of genetic variation in metagenomes remains challenging. Major factors that hamper the widespread application of variant-calling analysis include low-depth sequencing of individual genomes (which is especially significant for the microorganisms present in low abundance), the existence of large genomic variation even within the same species, the absence of comprehensive reference genomes, and the noise introduced by next-generation sequencing errors. Some bioinformatics tools, such as metaSNV or InStrain, have been created to identify genetic variants in metagenomes, but the performance of these tools has not been systematically assessed or compared with the variant callers commonly used on single or pooled genomes. In this study, we benchmark seven bioinformatic tools for genetic variant calling in metagenomics data and assess their performance. To do so, we simulated metagenomic reads to mimic human microbial composition, sequencing errors, and genetic variability. We also simulated different conditions, including low and high depth of coverage and unique or multiple strains per species. Our analysis of the simulated data shows that probabilistic method-based tools such as HaplotypeCaller and Mutect2 from the GATK toolset show the best performance. By applying these tools to longitudinal gut microbiome data from the Human Microbiome Project, we show that the genetic similarity between longitudinal samples from the same individuals is significantly greater than the similarity between samples from different individuals. Our benchmark shows that probabilistic tools can be used to call metagenomes, and we recommend the use of GATK's tools as reliable variant callers for metagenomic samples.

Utilization of low-molecular-weight organic compounds by the filterable fraction of a lotic microbiome

Filterable microorganisms participate in dissolved organic carbon (DOC) cycling in freshwater systems, however their exact functional role remains unknown. We determined the taxonomic identity and community dynamics of prokaryotic microbiomes in the 0.22 µm-filtered fraction and unfiltered freshwater from the Conwy River (North Wales, UK) in microcosms and, using targeted metabolomics and 14C-labelling, examined their role in the utilization of amino acids, organic acids and sugars spiked at environmentally-relevant (nanomolar) concentrations. To identify changes in community structure, we used 16S rRNA amplicon and shotgun sequencing. Unlike the unfiltered water samples where the consumption of DOC was rapid, the filtered fraction showed a 3-day lag phase before the consumption started. Analysis of functional categories of clusters of orthologous groups of proteins (COGs) showed that COGs associated with energy production increased in number in both fractions with substrate addition. The filtered fraction utilized low-molecular-weight (LMW) DOC at much slower rates than the whole community. Addition of nanomolar concentrations of LMW DOC did not measurably influence the composition of the microbial community nor the rate of consumption across all substrate types in either fraction. We conclude that due to their low activity, filterable microorganisms play a minor role in LMW DOC processing within a short residence time of lotic freshwater systems.

Microbiomes in supragingival biofilms and saliva of adolescents with gingivitis and gingival health

BACKGROUND

Important alterations exist in the microbiomes of supragingival biofilm and saliva samples from adolescent patients developing induced or spontaneous gingivitis relative to healthy controls. These and the relationships to dental health are not fully understood yet.

SUBJECTS AND METHODS

Supragingival biofilm samples (n = 36) were collected from the teeth of 9 adolescents with gingivitis induced by orthodontic appliances, as well as dental plaques (n = 40) from 10 adolescents with spontaneous gingivitis, in addition to similar samples (n = 36) from 9 healthy controls. The bacterial metagenomes were analyzed by 16S rRNA gene amplicon sequencing. Salivary microbiomes of the same persons were characterized by shotgun metagenome sequencing. The data sets were examined using advanced bioinformatics workflows and two reference databases.

RESULTS

The composition and diversity of bacterial communities did not differ extensively among the three study groups. Nevertheless, the relative abundances of the genera Fusobacterium, Akkermansia, Treponema, and Campylobacter were prominently higher in gingivitis patients versus controls. In contrast, the genera Lautropia, Kingella, Neisseria, Actinomyces, and Rothia were significantly more abundant in controls than in either of the two gingivitis groups.

CONCLUSIONS

The abundance pattern of certain taxa rather than individual strains shows characteristic features of potential diagnostic value. Stringent bioinformatics treatment of the sequencing data is mandatory to avoid unintentional misinterpretations.

A library preparation optimized for metagenomics of RNA viruses

Our understanding of the viral communities associated to animals has not yet reached the level attained on the bacteriome. This situation is due to, among others, technical challenges in adapting metagenomics using high-throughput sequencing to the study of RNA viromes in animals. Although important developments have been achieved in most steps of viral metagenomics, there is yet a key step that has received little attention: the library preparation. This situation differs from bacteriome studies in which developments in library preparation have largely contributed to the democratisation of metagenomics. Here, we present a library preparation optimized for metagenomics of RNA viruses from insect vectors of viral diseases. The library design allows a simple PCR-based preparation, such as those routinely used in bacterial metabarcoding, that is adapted to shotgun sequencing as required in viral metagenomics. We first optimized our library preparation using mock viral communities and then validated a full metagenomic approach incorporating our preparation in two pilot studies with field-caught insect vectors; one including a comparison with a published metagenomic protocol. Our approach provided a fold increase in virus-like sequences compared to other studies, and nearly-full genomes from new virus species. Moreover, our results suggested conserved trends in virome composition within a population of a mosquito species. Finally, the sensitivity of our approach was compared to a commercial diagnostic PCR for the detection of an arbovirus in field-caught insect vectors. Our approach could facilitate studies on viral communities from animals and the democratization of metagenomics in community ecology of viruses.

Dysbiosis of the Human Oral Microbiome During the Menstrual Cycle and Vulnerability to the External Exposures of Smoking and Dietary Sugar

Physiological hormonal fluctuations exert endogenous pressures on the structure and function of the human microbiome. As such, the menstrual cycle may selectively disrupt the homeostasis of the resident oral microbiome, thus compromising oral health. Hence, the aim of the present study was to structurally and functionally profile the salivary microbiome of 103 women in reproductive age with regular menstrual cycle, while evaluating the modifying influences of hormonal contraceptives, sex hormones, diet, and smoking. Whole saliva was sampled during the menstrual, follicular, and luteal phases (n = 309) of the cycle, and the participants reported questionnaire-based data concerning their life habits and oral or systemic health. No significant differences in alpha-diversity or phase-specific clustering of the overall microbiome were observed. Nevertheless, the salivary abundances of genera Campylobacter, Haemophilus, Prevotella, and Oribacterium varied throughout the cycle, and a higher species-richness was observed during the luteal phase. While the overall community structure maintained relatively intact, its functional properties were drastically affected. In particular, 11 functional modules were differentially abundant throughout the menstrual cycle, including pentose phosphate metabolism, and biosynthesis of cobalamin and neurotransmitter gamma-aminobutyric acid. The menstrual cycle phase, but not oral contraceptive usage, was accountable for greater variations in the metabolic pathways of the salivary microbiome. Further co-risk factor analysis demonstrated that Prevotella and Veillonella were increased in current smokers, whereas high dietary sugar consumption modified the richness and diversity of the microbiome during the cycle. This is the first large study to systematically address dysbiotic variations of the oral microbiome during the course of menstrual cycle, and document the additive effect of smoking and sugar consumption as environmental risk factors. It reveals the structural resilience and functional adaptability of the oral microbiome to the endogenous hormonal pressures of the menstrual cycle, while revealing its vulnerability to the exogenous exposures of diet and smoking.

The Composition and Metabolic Potential of the Human Small Intestinal Microbiota Within the Context of Inflammatory Bowel Disease

BACKGROUND AND AIMS

The human gastrointestinal tract harbours distinct microbial communities essential for health. Little is known about small intestinal communities, despite the small intestine playing a fundamental role in nutrient absorption and host-microbe immune homeostasis. We aimed to explore the small intestine microbial composition and metabolic potential, in the context of inflammatory bowel disease [IBD].

METHODS

Metagenomes derived from faecal samples and extensive phenotypes were collected from 57 individuals with an ileostomy or ileoanal pouch, and compared with 1178 general population and 478 IBD faecal metagenomes. Microbiome features were identified using MetaPhAn2 and HUMAnN2, and association analyses were performed using multivariate linear regression.

RESULTS

Small intestinal samples had a significantly lower bacterial diversity, compared with the general population and, to a lesser extent, IBD samples. Comparing bacterial composition, small intestinal samples clustered furthest from general population samples and closest to IBD samples with intestinal resections. Veillonella atypica, Streptococcus salivarius, and Actinomyces graevenitzii were among the species significantly enriched in the small intestine. Predicted metabolic pathways in the small intestine are predominantly involved in simple carbohydrate and energy metabolism, but also suggest a higher pro-inflammatory potential.

CONCLUSIONS

We described the bacterial composition and metabolic potential of the small intestinal microbiota. The colonic microbiome of IBD patients, particularly with intestinal resections, showed resemblance to that of the small intestine. Moreover, several features characterising the small intestinal microbiome have been previously associated with IBD. These results highlight the importance of studying the small intestinal microbiota to gain new insight into disease pathogenesis.

Quantitative analysis of the splice variants expressed by the major hepatitis B virus genotypes

Hepatitis B virus (HBV) is a major human pathogen that causes liver diseases. The main HBV RNAs are unspliced transcripts that encode the key viral proteins. Recent studies have shown that some of the HBV spliced transcript isoforms are predictive of liver cancer, yet the roles of these spliced transcripts remain elusive. Furthermore, there are nine major HBV genotypes common in different regions of the world, these genotypes may express different spliced transcript isoforms. To systematically study the HBV splice variants, we transfected human hepatoma cells, Huh7, with four HBV genotypes (A2, B2, C2 and D3), followed by deep RNA-sequencing. We found that 13-28 % of HBV RNAs were splice variants, which were reproducibly detected across independent biological replicates. These comprised 6 novel and 10 previously identified splice variants. In particular, a novel, singly spliced transcript was detected in genotypes A2 and D3 at high levels. The biological relevance of these splice variants was supported by their identification in HBV-positive liver biopsy and serum samples, and in HBV-infected primary human hepatocytes. Interestingly the levels of HBV splice variants varied across the genotypes, but the spliced pregenomic RNA SP1 and SP9 were the two most abundant splice variants. Counterintuitively, these singly spliced SP1 and SP9 variants had a suboptimal 5' splice site, supporting the idea that splicing of HBV RNAs is tightly controlled by the viral post-transcriptional regulatory RNA element.

Epipelagic microbiome of the Small Aral Sea: Metagenomic structure and ecological diversity

Microbial diversity studies regarding the aquatic communities that experienced or are experiencing environmental problems are essential for the comprehension of the remediation dynamics. In this pilot study, we present data on the phylogenetic and ecological structure of microorganisms from epipelagic water samples collected in the Small Aral Sea (SAS). The raw data were generated by massive parallel sequencing using the shotgun approach. As expected, most of the identified DNA sequences belonged to Terrabacteria and Actinobacteria (40% and 37% of the total reads, respectively). The occurrence of Deinococcus-Thermus, Armatimonadetes, Chloroflexi in the epipelagic SAS waters was less anticipated. Surprising was also the detection of sequences, which are characteristic for strict anaerobes-Ignavibacteria, hydrogen-oxidizing bacteria, and archaeal methanogenic species. We suppose that the observed very broad range of phylogenetic and ecological features displayed by the SAS reads demonstrates a more intensive mixing of water masses originating from diverse ecological niches of the Aral-Syr Darya River basin than presumed before.