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Abstract While rapid demographic changes in Asia are driving the incidence of chronic aging-related diseases, the limited availability of high-quality in vivo data hampers our ability to understand complex multi-factorial contributions, including gut microbial, to healthy aging. Leveraging a well-phenotyped cohort of community-living octogenarians in Singapore, we used deep shotgun-metagenomic sequencing for high-resolution taxonomic and functional characterization of their gut microbiomes (n = 234). Joint species-level analysis with other Asian cohorts identified distinct age-associated shifts characterized by reduction in microbial richness, and specific Alistipes and Bacteroides species enrichment (e.g., Alistipes shahii and Bacteroides xylanisolvens). Functional analysis confirmed these changes correspond to metabolic potential expansion in aging towards alternate pathways synthesizing and utilizing amino-acid precursors, vis-à-vis dominant microbial guilds producing butyrate in gut from pyruvate (e.g., Faecalibacterium prausnitzii, Roseburia inulinivorans). Extending these observations to key clinical markers helped identify >10 robust microbial associations to inflammation, cardiometabolic and liver health, including potential probiotic species (e.g., Parabacteroides goldsteinii) and pathobionts (e.g., Klebsiella pneumoniae), highlighting the microbiome’s role as biomarkers and potential targets for promoting healthy aging.

Abstract Background With the rapid increase in throughput of long-read sequencing technologies, recent studies have explored their potential for taxonomic classification by using alignment-based approaches to reduce the impact of higher sequencing error rates. While alignment-based methods are generally slower, k-mer-based taxonomic classifiers can overcome this limitation, potentially at the expense of lower sensitivity for strains and species that are not in the database. Results We present MetageNN, a memory-efficient long-read taxonomic classifier that is robust to sequencing errors and missing genomes. MetageNN is a neural network model that uses short k-mer profiles of sequences to reduce the impact of distribution shifts on error-prone long reads. Benchmarking MetageNN against other machine learning approaches for taxonomic classification (GeNet) showed substantial improvements with long-read data (20% improvement in F1 score). By utilizing nanopore sequencing data, MetageNN exhibits improved sensitivity in situations where the reference database is incomplete. It surpasses the alignment-based MetaMaps and MEGAN-LR, as well as the k-mer-based Kraken2 tools, with improvements of 100%, 36%, and 23% respectively at the read-level analysis. Notably, at the community level, MetageNN consistently demonstrated higher sensitivities than the previously mentioned tools. Furthermore, MetageNN requires 7× faster than MetaMaps and GeNet and > 2× faster than MEGAN-LR and MMseqs2. Conclusion This proof of concept work demonstrates the utility of machine-learning-based methods for taxonomic classification using long reads. MetageNN can be used on sequences not classified by conventional methods and offers an alternative approach for memory-efficient classifiers that can be optimized further.

Abstract Background Cholangiocarcinoma (CCA) is a fatal cancer of the bile duct with a poor prognosis owing to limited therapeutic options. The incidence of intrahepatic CCA (iCCA) is increasing worldwide, and its molecular basis is emerging. Environmental factors may contribute to regional differences in the mutation spectrum of European patients with iCCA, which are underrepresented in systematic genomic and transcriptomic studies of the disease. Methods We describe an integrated whole‐exome sequencing and transcriptomic study of 37 iCCAs patients in Germany. Results We observed as most frequently mutated genes ARID1A (14%), IDH1, BAP1, TP53, KRAS, and ATM in 8% of patients. We identified FGFR2::BICC1 fusions in two tumours, and FGFR2::KCTD1 and TMEM106B::ROS1 as novel fusions with potential therapeutic implications in iCCA and confirmed oncogenic properties of TMEM106B::ROS1 in vitro. Using a data integration framework, we identified PBX1 as a novel central regulatory gene in iCCA. We performed extended screening by targeted sequencing of an additional 40 CCAs. In the joint analysis, IDH1 (13%), BAP1 (10%), TP53 (9%), KRAS (7%), ARID1A (7%), NF1 (5%), and ATM (5%) were the most frequently mutated genes, and we found PBX1 to show copy gain in 20% of the tumours. According to other studies, amplifications of PBX1 tend to occur in European iCCAs in contrast to liver fluke‐associated Asian iCCAs. Conclusions By analyzing an additional European cohort of iCCA patients, we found that PBX1 protein expression was a marker of poor prognosis. Overall, our findings provide insight into key molecular alterations in iCCA, reveal new targetable fusion genes, and suggest that PBX1 is a novel modulator of this disease.

Abstract Background Long reads have gained popularity in the analysis of metagenomics data. Therefore, we comprehensively assessed metagenomics classification tools on the species taxonomic level. We analysed kmer-based tools, mapping-based tools and two general-purpose long reads mappers. We evaluated more than 20 pipelines which use either nucleotide or protein databases and selected 13 for an extensive benchmark. We prepared seven synthetic datasets to test various scenarios, including the presence of a host, unknown species and related species. Moreover, we used available sequencing data from three well-defined mock communities, including a dataset with abundance varying from 0.0001 to 20% and six real gut microbiomes. Results General-purpose mappers Minimap2 and Ram achieved similar or better accuracy on most testing metrics than best-performing classification tools. They were up to ten times slower than the fastest kmer-based tools requiring up to four times less RAM. All tested tools were prone to report organisms not present in datasets, except CLARK-S, and they underperformed in the case of the high presence of the host’s genetic material. Tools which use a protein database performed worse than those based on a nucleotide database. Longer read lengths made classification easier, but due to the difference in read length distributions among species, the usage of only the longest reads reduced the accuracy. The comparison of real gut microbiome datasets shows a similar abundance profiles for the same type of tools but discordance in the number of reported organisms and abundances between types. Most assessments showed the influence of database completeness on the reports. Conclusion The findings indicate that kmer-based tools are well-suited for rapid analysis of long reads data. However, when heightened accuracy is essential, mappers demonstrate slightly superior performance, albeit at a considerably slower pace. Nevertheless, a combination of diverse categories of tools and databases will likely be necessary to analyse complex samples. Discrepancies observed among tools when applied to real gut datasets, as well as a reduced performance in cases where unknown species or a significant proportion of the host genome is present in the sample, highlight the need for continuous improvement of existing tools. Additionally, regular updates and curation of databases are important to ensure their effectiveness.

ABSTRACTRecently discovered tet(X) gene variants have provided new insights into microbial antibiotic resistance mechanisms and their potential consequences for public health. This study focused on detection, analysis, and characterization of Tet(X4)-positive Enterobacterales from the gut microbiota of a healthy cohort of individuals in Singapore using cultivation-dependent and cultivation-independent approaches. Twelve Tet(X4)-positive Enterobacterales strains that were previously obtained from the cohort were fully genome-sequenced and comparatively analyzed. A metagenomic sequencing (MS) data set of the same samples was mined for contigs that harbored the tet(X4) resistance gene. The sequences of tet(X4)-containing contigs and plasmids sequences were compared. The presence of the resistance genes floR and estT (previously annotated as catD) was detected in the same cassette in 10 and 12 out of the 12 tet(X4)-carrying plasmids, respectively. MS detected tet(X4)-containing contigs in 2 out of the 109 subjects, while cultivation-dependent analysis previously reported a prevalence of 10.1%. The tet(X4)-containing sequences assembled from MS data are relatively short (~14 to 33 kb) but show high similarity to the respective plasmid sequences of the isolates. Our findings show that MS can complement efforts in the surveillance of antibiotic resistance genes for clinical samples, while it has a lower sensitivity than a cultivation-based method when the target organism has a low abundance. Further optimization is required if MS is to be utilized in antibiotic resistance surveillance.IMPORTANCEThe global rise in antibiotic resistance makes it necessary to develop and apply new approaches to detect and monitor the prevalence of antibiotic resistance genes in human populations. In this regard, of particular interest are resistances against last-resort antibiotics, such as tigecycline. In this study, we show that metagenomic sequencing can help to detect high abundance of the tigecycline resistance gene tet(X4) in fecal samples from a cohort of healthy human subjects. However, cultivation-based approaches currently remain the most reliable and cost-effective method for detection of antibiotic-resistant bacteria.

ABSTRACT The gut microbiota is inextricably linked to human health and disease. It can confer colonization resistance against invading pathogens either through niche occupation and nutrient competition or via its secreted metabolites. Short-chain fatty acids (SCFA) are the primary metabolites in the gut as a result of dietary fiber fermentation by the gut microbiota. In this work, we demonstrate that the interaction of single-species gut commensals on solid media is insufficient for pathogen inhibition, but supernatants from monocultures of these commensal bacteria enriched in acetate confer inhibition against anaerobic growth of the enteric pathogen Klebsiella pneumoniae. The three primary SCFAs (acetate, propionate, and butyrate) strongly inhibit the intestinal commensal Escherichia coli Nissle as well as a panel of enteric pathogens besides K. pneumoniae at physiological pH of the cecum and ascending colon. This inhibition was significantly milder on anaerobic gut commensals Bacteroides thetaiotaomicron and Bifidobacterium adolescentis previously demonstrated to be associated with microbiota recovery after antibiotic-induced dysbiosis. We describe a general suppression of bacterial membrane potential by these SCFAs at physiological cecum and ascending colonic pH. Furthermore, the strength of bacterial inhibition increases with increasing alkyl chain length. Overall, the insights gained in this study shed light on the potential therapeutic use of SCFAs for conferring colonization resistance against invading pathogens in a dysbiotic gut.IMPORTANCERising antimicrobial resistance has made treatment of bacterial infections increasingly difficult. According to the World Health Organization, it has become a burgeoning threat to hospital and public health systems worldwide. This threat is largely attributed to the global rise of carbapenem-resistant Enterobacteriaceae in recent years, with common hospital-acquired pathogens growing increasingly resistant to last-line antibiotics. Antibiotics disrupt the homeostatic balance of the gut microbiota, resulting in the loss of colonization resistance against enteric pathogens. This work describes the ability of short-chain fatty acids (SCFAs) produced by gut microbiota to be effective against a wide panel of enteric pathogens without major impact on common gut commensal species. We also demonstrate a previously undescribed link between alkyl chain length and antibacterial effects of SCFAs. SCFAs, thus, hold promise as an alternative therapeutic option leveraging on the antimicrobial activity of these endogenously produced gut metabolites without disrupting gut microbiota homeostasis.

Reference genomes for gut microbiomes help unravel microbial “dark matter” and serve as valuable resource for disease-focused studies. Here, the authors perform short and long read metagenomics and metagenome-assembled genomes analyses to profile the gut microbiome of Southeast Asian populations, revealing significant species and strain-level diversity, with thousands of previously uncharacterized biosynthetic gene clusters.

Genome assembly and metabolomic analysis of Singapore’s national flower, Papilionanthe (Ple.) Miss Joaquim “Agnes” (PMJ), expands the known genetic repertoire of the Orchidaceae family and insights into the biochemical processes of PMJ.

Abstract Background The transient and fragmented nature of the deep-sea hydrothermal environment made of ridge subduction, plate collision and the emergence of new rifts is currently acting to separate of vent populations, promoting local adaptation and contributing to bursts of speciation and species specialization. The tube-dwelling worms Alvinella pompejana called the Pompeii worm and its sister species A. caudata live syntopically on the hottest part of deep-sea hydrothermal chimneys along the East Pacific Rise. They are exposed to extreme thermal and chemical gradients, which vary greatly in space and time, and thus represent ideal candidates for understanding the evolutionary mechanisms at play in the vent fauna evolution. Results We explored genomic patterns of divergence in the early and late stages of speciation of these emblematic worms using transcriptome assemblies and the first draft genome to better understand the relative role of geographic isolation and habitat preference in their genome evolution. Analyses were conducted on allopatric populations of Alvinella pompejana (early stage of separation) and between A. pompejana and its syntopic species Alvinella caudata (late stage of speciation). We first identified divergent genomic regions and targets of selection as well as their position in the genome over collections of orthologous genes and, then, described the speciation dynamics by documenting the annotation of the most divergent and/or positively selected genes involved in the isolation process. Gene mapping clearly indicated that divergent genes associated with the early stage of speciation, although accounting for nearly 30% of genes, are highly scattered in the genome without any island of divergence and not involved in gamete recognition or mito-nuclear incompatibilities. By contrast, genomes of A. pompejana and A. caudata are clearly separated with nearly all genes (96%) exhibiting high divergence. This congealing effect however seems to be linked to habitat specialization and still allows positive selection on genes involved in gamete recognition, as a possible long-duration process of species reinforcement. Conclusion Our analyses highlight the non-negligible role of natural selection on both the early and late stages of speciation in the iconic thermophilic worms living on the walls of deep-sea hydrothermal chimneys. They shed light on the evolution of gene divergence during the process of speciation and species specialization over a very long period of time.

Dissemination of carbapenemase-encoding plasmids by horizontal gene transfer in multidrug-resistant bacteria is the major driver of rising carbapenem-resistance, but the conjugative mechanics and evolution of clinically relevant plasmids are not yet clear. We performed whole-genome sequencing on 1,215 clinical Enterobacterales isolates collected in Singapore during 2010–2015. We identified 1,126 carbapenemase-encoding plasmids and discovered pKPC2 is becoming the dominant plasmid in Singapore, overtaking an earlier dominant plasmid, pNDM1. pKPC2 frequently conjugates with many Enterobacterales species, including hypervirulent Klebsiella pneumoniae, and maintains stability in vitro without selection pressure and minimal adaptive sequence changes. Furthermore, capsule and decreasing taxonomic relatedness between donor and recipient pairs are greater conjugation barriers for pNDM1 than pKPC2. The low fitness costs pKPC2 exerts in Enterobacterales species indicate previously undetected carriage selection in other ecological settings. The ease of conjugation and stability of pKPC2 in hypervirulent K. pneumoniae could fuel spread into the community.

Abstract Hypercholesterolemia is becoming a problem with increasing significance. Dietary vegetable oils may help to improve this condition due to presence of phytonutrients with potentially synergistic cholesterol-lowering effects. The objective of this 8-week double-blinded randomized clinical trial was to investigate the effects of consuming 30 g of two different blended cooking oils, rich in omega-3 alpha-linolenic acid and phytonutrients, or refined olive oil on the intestinal microbiota in 126 volunteers with borderline hypercholesterolemia. Multi-factor analysis of relationships between the gut microbiota composition at various taxonomic ranks and the clinical trial parameters revealed the association between beneficial effects of the dietary intervention on the blood lipid profile with abundance of Clostridia class of the gut microbiota. This microbiota feature was upregulated in the course of the dietary intervention and associated with various plasma markers of metabolic health status, such as Triglycerides, Apolipoprotein B and Total Cholesterol to HDL ratio in a beneficial way. The relative abundance of a single species—Clostridium leptum—highly increased during the dietary intervention in all the three study groups. The oil blend with the highest concentration of omega-3 PUFA is associated with faster and more robust responses of the intestinal microbiota, including elevation of alpha-diversity. Butyrate production is being discussed as a plausible process mediating the observed beneficial influence on the plasma lipid profile. Causal mediation analysis suggested that Clostridium genus rather than the higher rank of the phylogeny—Clostridia class—may be involved in the diet-induced improvements of the blood lipid profile.

Abstract While understanding molecular heterogeneity across patients underpins precision oncology, there is increasing appreciation for taking intra-tumor heterogeneity into account. Based on large-scale analysis of cancer omics datasets, we highlight the importance of intra-tumor transcriptomic heterogeneity (ITTH) for predicting clinical outcomes. Leveraging single-cell RNA-seq (scRNA-seq) with a recommender system (CaDRReS-Sc), we show that heterogeneous gene-expression signatures can predict drug response with high accuracy (80%). Using patient-proximal cell lines, we established the validity of CaDRReS-Sc’s monotherapy (Pearson r>0.6) and combinatorial predictions targeting clone-specific vulnerabilities (>10% improvement). Applying CaDRReS-Sc to rapidly expanding scRNA-seq compendiums can serve as in silico screen to accelerate drug-repurposing studies. Availability: https://github.com/CSB5/CaDRReS-Sc .

Shigella flexneri is a major diarrhoeal pathogen, and the emergence of multidrug-resistant S. flexneri is of public health concern. We report the detection of a clonal cluster of multidrug-resistant serotype 1c (7a) S. flexneri in Singapore in April 2022. Long-read whole-genome sequence analysis found five S. flexneri isolates to be clonal and harboring the extended-spectrum β-lactamases blaCTX−M−15 and blaTEM−1. The isolates were phenotypically resistant to ceftriaxone and had intermediate susceptibility to ciprofloxacin. The S. flexneri clonal cluster was first detected in a tertiary hospital diagnostic laboratory (sentinel-site), to which the S. flexneri isolates were sent from other hospitals for routine serogrouping. Long-read whole-genome sequence analysis was performed in the sentinel-site near real-time in view of the unusually high number of S. flexneri isolates received within a short time frame. This study demonstrates that near real-time sentinel-site sequence-based surveillance of convenience samples can detect possible clonal outbreak clusters and may provide alerts useful for public health mitigations at the earliest possible opportunity.

Objectives: Hypermucoviscous Klebsiella pneumoniae is an emerging cause of community-acquired liver abscess. The aim of this study was to investigate whether hypermucoviscous strains could be shared among households. Methods: The clinical K. pneumoniae isolates from a cohort of 24 patients with Klebsiella liver abscess were genotyped, and the stool metagenomes of the index patients and their cohabiting domestic partners were analyzed. Results: K. pneumoniae was identified in 33% of index patient stools, and one index patient’s clinical isolate was identified in their domestic partner’s stool. Conclusions: This could represent a transmission event or could represent exposure to a common environmental source.

Abstract Background Whole genome sequencing of cultured pathogens is the state of the art public health response for the bioinformatic source tracking of illness outbreaks. Quasimetagenomics can substantially reduce the amount of culturing needed before a high quality genome can be recovered. Highly accurate short read data is analyzed for single nucleotide polymorphisms and multi-locus sequence types to differentiate strains but cannot span many genomic repeats, resulting in highly fragmented assemblies. Long reads can span repeats, resulting in much more contiguous assemblies, but have lower accuracy than short reads. Results We evaluated the accuracy of Listeria monocytogenes assemblies from enrichments (quasimetagenomes) of naturally-contaminated ice cream using long read (Oxford Nanopore) and short read (Illumina) sequencing data. Accuracy of ten assembly approaches, over a range of sequencing depths, was evaluated by comparing sequence similarity of genes in assemblies to a complete reference genome. Long read assemblies reconstructed a circularized genome as well as a 71 kbp plasmid after 24 h of enrichment; however, high error rates prevented high fidelity gene assembly, even at 150X depth of coverage. Short read assemblies accurately reconstructed the core genes after 28 h of enrichment but produced highly fragmented genomes. Hybrid approaches demonstrated promising results but had biases based upon the initial assembly strategy. Short read assemblies scaffolded with long reads accurately assembled the core genes after just 24 h of enrichment, but were highly fragmented. Long read assemblies polished with short reads reconstructed a circularized genome and plasmid and assembled all the genes after 24 h enrichment but with less fidelity for the core genes than the short read assemblies. Conclusion The integration of long and short read sequencing of quasimetagenomes expedited the reconstruction of a high quality pathogen genome compared to either platform alone. A new and more complete level of information about genome structure, gene order and mobile elements can be added to the public health response by incorporating long read analyses with the standard short read WGS outbreak response.

ABSTRACT Immunocompromised hosts with prolonged severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections have been implicated in the emergence of highly mutated SARS-CoV-2 variants. Spike mutations are of particular concern because the spike protein is a key target for vaccines and therapeutics for SARS-CoV-2. Here, we report the emergence of spike mutations in two immunocompromised patients with persistent SARS-CoV-2 reverse transcription (RT)-PCR positivity (>90 days). Whole-genome sequence analysis of samples obtained before and after coronavirus disease 2019 (COVID-19) treatment demonstrated the development of partial therapeutic escape mutations and increased intrahost SARS-CoV-2 genome diversity over time. This case series thus adds to the accumulating evidence that immunocompromised hosts with persistent infections are important sources of SARS-CoV-2 genome diversity and, in particular, clinically important spike protein diversity. IMPORTANCE The emergence of clinically important mutations described in this report highlights the need for sustained vigilance and containment measures when managing immunocompromised patients with persistent COVID-19. Even as jurisdictions across the globe start lifting pandemic control measures, immunocompromised patients with persistent COVID-19 constitute a unique group that requires close genomic monitoring and enhanced infection control measures, to ensure early detection and containment of mutations and variants of therapeutic and public health importance.

Abstract Background This study aims to characterize, the gut and oral microbiome in Asian subjects with Crohn’s disease (CD) using whole genome shotgun sequencing, thereby allowing for strain-level comparison. Methods A case–control study with age, sex and ethnicity matched healthy controls was conducted. CD subjects were limited to well-controlled patients without oral manifestations. Fecal and saliva samples were collected for characterization of gut and oral microbiome respectively. Microbial DNA were extracted, libraries prepared and sequenced reads profiled. Taxonomic diversity, taxonomic association, strain typing and microbial gene pathway analyses were conducted. Results The study recruited 25 subjects with CD and 25 healthy controls. The oral microbe Streptococcus salivarius was found to be enriched and of concordant strains in the gut and oral microbiome of Crohn’s disease subjects. This was more likely in CD subjects with higher Crohn’s Disease Activity Index (184.3 ± 2.9 vs 67.1 ± 82.5, p = 0.012) and active disease status (Diarrhoea/abdominal pain/blood-in-stool/fever and fatigue) (p = 0.016). Gut species found to be significantly depleted in CD compared to control (Relative abundance: Median[Range]) include: Faecalibacterium prausnitzii (0.03[0.00–4.56] vs 13.69[5.32–18.71], p = 0.010), Roseburia inulinivorans (0.00[0.00–0.03] vs 0.21[0.01–0.53], p = 0.010) and Alistipes senegalensis (0.00[0.00–0.00] vs 0.00[0.00–0.02], p = 0.029). While Clostridium nexile (0.00[0.00–0.12] vs 0.00[0.00–0.00], p = 0.038) and Ruminococcus gnavus (0.43[0.02–0.33] vs 0.00[0.00–0.13], p = 0.043) were found to be enriched. C. nexile enrichment was not found in CD subjects of European descent. Microbial arginine (Linear-discriminant-analysis: 3.162, p = 0.001) and isoprene (Linear-discriminant-analysis: 3.058, p

ABSTRACT Rapid onsite whole-genome sequencing of two suspected severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) N gene diagnostic escape samples revealed a previously unreported N gene point mutation at genome position 29195. Because the G29195T mutation occurs within a region probed by a commonly referenced U.S. CDC N gene reverse transcription (RT)-PCR assay, we hypothesize that the G29195T mutation rendered the N gene target of a proprietary commercial assay undetectable. The putative diagnostic escape G29195T mutation demonstrates the need for nearly real-time surveillance, as emergence of a novel SARS-CoV-2 variant with the potential to escape diagnostic tests continues to be a threat. IMPORTANCE Accurate diagnostic detection of SARS-CoV-2 currently depends on the large-scale deployment of RT-PCR assays. SARS-CoV-2 RT-PCR assays target predetermined regions in the viral genomes by complementary binding of primers and probes to nucleic acid sequences in the clinical samples. Potential diagnostic escapes, such as those of clinical samples harboring the G29195T mutation, may result in false-negative SARS-CoV-2 RT-PCR results. The rapid detection and sharing of potential diagnostic escapes are essential for diagnostic laboratories and manufacturers around the world, to optimize their assays as SARS-CoV-2 continues to evolve.

To determine the duration of carbapenemase-producing Enterobacteriaceae (CPE) carriage, we studied 21 CPE carriers for »1 year. Mean carriage duration was 86 days; probability of decolonization in 1 year was 98.5%, suggesting that CPE-carriers’ status can be reviewed yearly. Prolonged carriage was associated with use of antimicrobial drugs.

Abstract Background As more animal studies start to disentangle pathways linking the gut microbial ecosystem and neurobehavioral traits, human studies have grown rapidly. Many have since investigated the bidirectional communication between the gastrointestinal tract and the central nervous system, specifically on the effects of microbial composition on the brain and development. Methods Our review at the initial stage aimed to evaluate literature on gut microbial alterations in pediatric neurobehavioral conditions. We searched five literature databases (Embase, PubMed, PsychInfo, Scopus, and Medline) and found 4489 published work. As the mechanisms linking gut microbiota to these conditions are divergent, the scope of this review was narrowed to focus on describing gut dysbiosis in children with autism spectrum disorder (ASD). Results Among the final 26 articles, there was a lack of consistency in the reported gut microbiome changes across ASD studies, except for distinguishable patterns, within limits, for Prevotella, Firmicutes at the phylum level, Clostridiales clusters including Clostridium perfringens, and Bifidobacterium species. Conclusions These results were inadequate to confirm a global microbiome change in children with ASD and causality could not be inferred to explain the etiology of the behaviors associated with ASD. Mechanistic studies are needed to elucidate the specific role of the gut microbiome in the pathogenesis of ASD.

Idiopathic granulomatous mastitis (IGM) is a rare and benign inflammatory breast disease with ambiguous aetiology. Contrastingly, lactational mastitis (LM) is commonly diagnosed in breastfeeding women. To investigate IGM aetiology, we profiled the microbial flora of pus and skin in patients with IGM and LM. A total of 26 patients with IGM and 6 patients with LM were included in the study. The 16S rRNA sequencing libraries were constructed from 16S rRNA gene amplified from total DNA extracted from pus and skin swabs in patients with IGM and LM controls. Constructed libraries were multiplexed and paired-end sequenced on HiSeq4000. Metagenomic analysis was conducted using modified microbiome abundance analysis suite customised R-resource for paired pus and skin samples. Microbiome multivariable association analyses were performed using linear models. A total of 21 IGM and 3 LM paired pus and skin samples underwent metagenomic analysis. Bray−Curtis ecological dissimilarity distance showed dissimilarity across four sample types (IGM pus, IGM skin, LM pus, and LM skin; PERMANOVA, p < 0.001). No characteristic dominant genus was observed across the IGM samples. The IGM pus samples were more diverse than corresponding IGM skin samples (Shannon and Simpson index; Wilcoxon paired signed-rank tests, p = 0.022 and p = 0.07). Corynebacterium kroppenstedtii, reportedly associated with IGM in the literature, was higher in IGM pus samples than paired skin samples (Wilcoxon, p = 0.022). Three other species and nineteen genera were statistically significant in paired IGM pus–skin comparison after antibiotic treatment adjustment and multiple comparisons correction. Microbial profiles are unique between patients with IGM and LM. Inter-patient variability and polymicrobial IGM pus samples cannot implicate specific genus or species as an infectious cause for IGM.

Background: The ongoing COVID-19 pandemic is a global health crisis caused by the spread of SARS-CoV-2. Establishing links between known cases is crucial for the containment of COVID-19. In the healthcare setting, the ability to rapidly identify potential healthcare-associated COVID-19 clusters is critical for healthcare worker and patient safety. Increasing sequencing technology accessibility has allowed routine clinical diagnostic laboratories to sequence SARS-CoV-2 in clinical samples. However, these laboratories often lack specialized informatics skills required for sequence analysis. Therefore, an on-site, intuitive sequence analysis tool that enables clinical laboratory users to analyze multiple genomes and derive clinically relevant information within an actionable timeframe is needed.Results: We propose CalmBelt, an integrated framework for on-site whole genome characterization and outbreak tracking. Nanopore sequencing technology enables on-site sequencing and construction of draft genomes for multiple SARS-CoV-2 samples within 12 h. CalmBelt's interactive interface allows users to analyse multiple SARS-CoV-2 genomes by utilizing whole genome information, collection date, and additional information such as predefined potential clusters from epidemiological investigations. CalmBelt also integrates established SARS-CoV-2 nomenclature assignments, GISAID clades and PANGO lineages, allowing users to visualize relatedness between samples together with the nomenclatures. We demonstrated multiple use cases including investigation of potential hospital transmission, mining transmission patterns in a large outbreak, and monitoring possible diagnostic-escape.Conclusions: This paper presents an on-site rapid framework for SARS-CoV-2 whole genome characterization. CalmBelt interactive web application allows non-technical users, such as routine clinical laboratory users in hospitals to determine SARS-CoV-2 variants of concern, as well as investigate the presence of potential transmission clusters. The framework is designed to be compatible with routine usage in clinical laboratories as it only requires readily available sample data, and generates information that impacts immediate infection control mitigations.

ConclusionBEEM-Static provides new opportunities for mining ecologically interpretable interactions and systems insights from the growing corpus of microbiome data.

Abstract Background Acrylic acid (AA) is a widely used commodity chemical derived from non-renewable fossil fuel sources. Alternative microbial-based production methodologies are being developed with the aim of providing “green” acrylic acid. These initiatives will benefit from component sensing tools that facilitate rapid and easy detection of in vivo AA production. Results We developed a novel transcriptional sensor facilitating in vivo detection of acrylic acid (AA). RNAseq analysis of Escherichia coli exposed to sub-lethal doses of acrylic acid identified a selectively responsive promoter (PyhcN) that was cloned upstream of the eGFP gene. In the presence of AA, eGFP expression in E. coli cells harbouring the sensing construct was readily observable by fluorescence read-out. Low concentrations of AA (500 μM) could be detected whilst the closely related lactic and 3-hydroxy propionic acids failed to activate the sensor. We further used the developed AA-biosensor for in vivo FACS-based screening and identification of amidase mutants with improved catalytic properties for deamination of acrylamide to acrylic acid. Conclusions The transcriptional AA sensor developed in this study will benefit strain, enzyme and pathway engineering initiatives targeting the efficient formation of bio-acrylic acid.

Abstract Background The dynamics of microbial communities is driven by a range of interactions from symbiosis to predator-prey relationships, the majority of which are poorly understood. With the increasing availability of high-throughput microbiome taxonomic profiling data, it is now conceivable to directly learn the ecological models that explicitly define microbial interactions and explain community dynamics. The applicability of these approaches is severely limited by the lack of accurate absolute cell density measurements (biomass). Methods We present a new computational approach that resolves this key limitation in the inference of generalized Lotka-Volterra models (gLVMs) by coupling biomass estimation and model inference with an expectation-maximization algorithm (BEEM). Results BEEM outperforms the state-of-the-art methods for inferring gLVMs, while simultaneously eliminating the need for additional experimental biomass data as input. BEEM’s application to previously inaccessible public datasets (due to the lack of biomass data) allowed us to construct ecological models of microbial communities in the human gut on a per-individual basis, revealing personalized dynamics and keystone species. Conclusions BEEM addresses a key bottleneck in “systems analysis” of microbiomes by enabling accurate inference of ecological models from high throughput sequencing data without the need for experimental biomass measurements.

Here, the authors provide detailed analyses of viral RNA structure in virions and in infected cells for four dengue virus serotypes and four Zika virus strains, and identify conserved structures that are important for virus replication.

Abstract Background Even though human sweat is odorless, bacterial growth and decomposition of specific odor precursors in it is believed to give rise to body odor in humans. While mechanisms of odor generation have been widely studied in adults, little is known for teenagers and pre-pubescent children who have distinct sweat composition from immature apocrine and sebaceous glands, but are arguably more susceptible to the social and psychological impact of malodor. Results We integrated information from whole microbiome analysis of multiple skin sites (underarm, neck, and head) and multiple time points (1 h and 8 h after bath), analyzing 180 samples in total to perform the largest metagenome-wide association study to date on malodor. Significant positive correlations were observed between odor intensity and the relative abundance of Staphylococcus hominis, Staphylococcus epidermidis, and Cutibacterium avidum, as well as negative correlation with Acinetobacter schindleri and Cutibacterium species. Metabolic pathway analysis highlighted the association of isovaleric and acetic acid production (sour odor) from enriched S. epidermidis (teen underarm) and S. hominis (child neck) enzymes and sulfur production from Staphylococcus species (teen underarm) with odor intensity, in good agreement with observed odor characteristics in pre-pubescent children and teenagers. Experiments with cultures on human and artificial sweat confirmed the ability of S. hominis and S. epidermidis to independently produce malodor with distinct odor characteristics. Conclusions These results showcase the power of skin metagenomics to study host-microbial co-metabolic interactions, identifying distinct pathways for odor generation from sweat in pre-pubescent children and teenagers and highlighting key enzymatic targets for intervention.

Summary: Growing evidence indicates a role for the gut microbiota in modulating anti-tumor treatment efficacy in human cancer. Here we study mucosa-associated invariant T (MAIT) cells to look for evidence of bacterial antigen recognition in human colon, lung, and kidney carcinomas. Using mass cytometry and single-cell mRNA sequencing, we identify a tumor-infiltrating MAIT cell subset expressing CD4 and Foxp3 and observe high expression of CD39 on MAIT cells from colorectal cancer (CRC) only, which we show in vitro to be expressed specifically after TCR stimulation. We further reveal that these cells are phenotypically and functionally exhausted. Sequencing data show high bacterial infiltration in CRC tumors and highlight an enriched species, Fusobacteria nucleatum, with capability to activate MAIT cells in a TCR-dependent way. Our results provide evidence of a MAIT cell response to microbial antigens in CRC and could pave the way for manipulating MAIT cells or the microbiome for cancer therapy.

Biodiversity is in crisis due to habitat destruction and climate change. The conservation of many noncharismatic species is hampered by the lack of data. Yet, natural history research-a major source of information on noncharismatic species-is in decline. We here suggest a remedy for many mammal species, i.e., metagenomic clean-up of fecal samples that are "crowdsourced" during routine field surveys. Based on literature data, we estimate that this approach could yield natural history information for circa 1,000 species within a decade. Metagenomic analysis would simultaneously yield natural history data on diet and gut parasites while enhancing our understanding of host genetics, gut microbiome, and the functional interactions between traditional and new natural history data. We document the power of this approach by carrying out a "metagenomic clean-up" on fecal samples collected during a single night of small mammal trapping in one of Alfred Wallace's favorite collecting sites.

Riboswitches recognize and respond to specific metabolites by altering gene expression. Here, the authors developed a high-throughput method (PARCEL) to experimentally identify RNA aptamers across transcriptomes.

Abstract Background Viral populations are complex, dynamic, and fast evolving. The evolution of groups of closely related viruses in a competitive environment is termed quasispecies. To fully understand the role that quasispecies play in viral evolution, characterizing the trajectories of viral genotypes in an evolving population is the key. In particular, long-range haplotype information for thousands of individual viruses is critical; yet generating this information is non-trivial. Popular deep sequencing methods generate relatively short reads that do not preserve linkage information, while third generation sequencing methods have higher error rates that make detection of low frequency mutations a bioinformatics challenge. Here we applied BAsE-Seq, an Illumina-based single-virion sequencing technology, to eight samples from four chronic hepatitis B (CHB) patients – once before antiviral treatment and once after viral rebound due to resistance. Results With single-virion sequencing, we obtained 248–8796 single-virion sequences per sample, which allowed us to find evidence for both hard and soft selective sweeps. We were able to reconstruct population demographic history that was independently verified by clinically collected data. We further verified four of the samples independently through PacBio SMRT and Illumina Pooled deep sequencing. Conclusions Overall, we showed that single-virion sequencing yields insight into viral evolution and population dynamics in an efficient and high throughput manner. We believe that single-virion sequencing is widely applicable to the study of viral evolution in the context of drug resistance and host adaptation, allows differentiation between soft or hard selective sweeps, and may be useful in the reconstruction of intra-host viral population demographic history.

Cholangiocarcinoma (CCA) is the primary cancer of the bile duct system. The role of bile duct tissue microbiomes in CCA tumorigenesis is unestablished. To address this, sixty primary CCA tumors and matched normals, from both liver fluke (Opisthorchis viverrini) associated (OVa, n = 28) and non-O. viverrini associated (non-OVa, n = 32) cancers, were profiled using high-throughput 16S rRNA sequencing. A distinct, tissue-specific microbiome dominated by the bacterial families Dietziaceae, Pseudomonadaceae and Oxalobacteraceae was observed in bile duct tissues. Systemic perturbation of the microbiome was noted in tumor and paired normal samples (vs non-cancer normals) for several bacterial families with a significant increase in Stenotrophomonas species distinguishing tumors vs paired normals. Comparison of parasite associated (OVa) vs non-associated (non-OVa) groups identified enrichment for specific enteric bacteria (Bifidobacteriaceae, Enterobacteriaceae and Enterococcaceae). One of the enriched families, Bifidobacteriaceae, was found to be dominant in the O. viverrini microbiome, providing a mechanistic link to the parasite. Functional analysis and comparison of CCA microbiomes revealed higher potential for producing bile acids and ammonia in OVa tissues, linking the altered microbiota to carcinogenesis. These results define how the unique microbial communities resident in the bile duct, parasitic infections and the tissue microenvironment can influence each other, and contribute to cancer.

Read mapping and alignment tools are critical for many applications based on MinION sequencers. Here, the authors present GraphMap, a mapping algorithm designed to analyze nanopore sequencing reads, that progressively refines candidate alignments to handle potentially high error rates to align long reads.

Barrett’s oesophagus is a precancerous intestinal metaplasia that can progress to oesophageal adenocarcinoma. In this study, the authors isolate and characterize human Barrett’s stem cells and identify a specific genomic pedigree that supports the potential role of these cells as precursors of oesophageal adenocarcinoma.

Genome rearrangements, a hallmark of cancer, can result in gene fusions with oncogenic properties. Using DNA paired-end-tag (DNA-PET) whole-genome sequencing, we analyzed 15 gastric cancers (GCs) from Southeast Asians. Rearrangements were enriched in open chromatin and shaped by chromatin structure. We identified seven rearrangement hot spots and 136 gene fusions. In three out of 100 GC cases, we found recurrent fusions between CLDN18, a tight junction gene, and ARHGAP26, a gene encoding a RHOA inhibitor. Epithelial cell lines expressing CLDN18-ARHGAP26 displayed a dramatic loss of epithelial phenotype and long protrusions indicative of epithelial-mesenchymal transition (EMT). Fusion-positive cell lines showed impaired barrier properties, reduced cell-cell and cell-extracellular matrix adhesion, retarded wound healing, and inhibition of RHOA. Gain of invasion was seen in cancer cell lines expressing the fusion. Thus, CLDN18-ARHGAP26 mediates epithelial disintegration, possibly leading to stomach H+ leakage, and the fusion might contribute to invasiveness once a cell is transformed.

The vast burden of cryptococcal meningitis occurs in immunosuppressed patients, driven by HIV, and is caused by Cryptococcus neoformans var. grubii. We previously reported cryptococcal meningitis in Vietnam arising atypically in HIV uninfected, apparently immunocompetent patients, caused by a single amplified fragment length polymorphism (AFLP) cluster of C. neoformans var. grubii (VNIγ). This variant was less common in HIV infected individuals; it remains unclear why this lineage is associated with apparently immunocompetent patients. To study this host tropism we aimed to further our understanding of clinical phenotype and genomic variation within Vietnamese C. neoformans var. grubii. After performing MLST on C. neoformans clinical isolates we identified 14 sequence types (STs); ST5 correlated with the VNIγ cluster. We next compared clinical phenotype by lineage and found HIV infected patients with cryptococcal meningitis caused by ST5 organisms were significantly more likely to have lymphadenopathy (11% vs. 4%, p = 0.05 Fisher's exact test) and higher blood lymphocyte count (median 0.76 versus 0.55 X109 cells/L, p = 0.001, Kruskal-Wallis test). Furthermore, survivors of ST5 infections had evidence of worse disability outcomes at 70 days (72.7% (40/55) in ST5 infections versus 57.1% (52/91) non-ST5 infections (OR 2.11, 95%CI 1.01 to 4.41), p = 0.046). To further investigate the relationship between strain and disease phenotype we performed genome sequencing on eight Vietnamese C. neoformans var. grubii. Eight genome assemblies exhibited >99% nucleotide sequence identity and we identified 165 kbp of lineage specific to Vietnamese isolates. ST5 genomes harbored several strain specific regions, incorporating 19 annotated coding sequences and eight hypothetical proteins. These regions included a phenolic acid decarboxylase, a DEAD-box ATP-dependent RNA helicase 26, oxoprolinases, a taurine catabolism dioxygenase, a zinc finger protein, membrane transport proteins and various drug transporters. Our work outlines the complexity of genomic pathogenicity in cryptococcal infections and identifies a number of gene candidates that may aid the disaggregation of the pathways associated with the pathogenesis of Cryptococcus neoformans var. grubii.

OBJECTIVE:Cell-free DNA from maternal plasma can be used for non-invasive prenatal testing for aneuploidies and single gene disorders, and also has applications as a biomarker for monitoring high-risk pregnancies, such as those at risk of pre-eclampsia. On average, the fractional cell-free fetal DNA concentration in plasma is approximately 15%, but can vary from less than 4% to greater than 30%. Although quantification of cell-free fetal DNA is straightforward in the case of a male fetus, there is no universal fetal marker; in a female fetus measurement is more challenging. We have developed a panel of multiplexed insertion/deletion polymorphisms that can measure fetal fraction in all pregnancies in a simple, targeted sequencing reaction. METHODS:A multiplex panel of primers was designed for 35 indels plus a ZFX/ZFY amplicon. cfDNA was extracted from plasma from 157 pregnant women, and maternal genomic DNA was extracted for 20 of these samples for panel validation. Sixty-one samples from pregnancies with a male fetus were subjected to whole genome sequencing on the Ion Proton sequencing platform, and fetal fraction derived from Y chromosome counts was compared to fetal fraction measured using the indel panel. A total of 157 cell-free DNA samples were sequenced using the indel panel, and informativity was assessed, along with the proportion of fetal DNA. RESULTS:Using gDNA we optimised the indel panel, removing amplicons giving rise to PCR bias. Good correlation was found between fetal fraction using indels and using whole genome sequencing of the Y chromosome (Spearmans r = 0.69). A median of 12 indels were informative per sample. The indel panel was informative in 157/157 cases (mean fetal fraction 14.4% (±0.58%)). CONCLUSIONS:Using our targeted next generation sequencing panel we can readily assess the fetal DNA percentage in male and female pregnancies.

Malassezia is a unique lipophilic genus in class Malasseziomycetes in Ustilaginomycotina, (Basidiomycota, fungi) that otherwise consists almost exclusively of plant pathogens. Malassezia are typically isolated from warm-blooded animals, are dominant members of the human skin mycobiome and are associated with common skin disorders. To characterize the genetic basis of the unique phenotypes of Malassezia spp., we sequenced the genomes of all 14 accepted species and used comparative genomics against a broad panel of fungal genomes to comprehensively identify distinct features that define the Malassezia gene repertoire: gene gain and loss; selection signatures; and lineage-specific gene family expansions. Our analysis revealed key gene gain events (64) with a single gene conserved across all Malassezia but absent in all other sequenced Basidiomycota. These likely horizontally transferred genes provide intriguing gain-of-function events and prime candidates to explain the emergence of Malassezia. A larger set of genes (741) were lost, with enrichment for glycosyl hydrolases and carbohydrate metabolism, concordant with adaptation to skin's carbohydrate-deficient environment. Gene family analysis revealed extensive turnover and underlined the importance of secretory lipases, phospholipases, aspartyl proteases, and other peptidases. Combining genomic analysis with a re-evaluation of culture characteristics, we establish the likely lipid-dependence of all Malassezia. Our phylogenetic analysis sheds new light on the relationship between Malassezia and other members of Ustilaginomycotina, as well as phylogenetic lineages within the genus. Overall, our study provides a unique genomic resource for understanding Malassezia niche-specificity and potential virulence, as well as their abundance and distribution in the environment and on human skin.

Dengue virus (DENV) infection of an individual human or mosquito host produces a dynamic population of closely-related sequences. This intra-host genetic diversity is thought to offer an advantage for arboviruses to adapt as they cycle between two very different host species, but it remains poorly characterized. To track changes in viral intra-host genetic diversity during horizontal transmission, we infected Aedes aegypti mosquitoes by allowing them to feed on DENV2-infected patients. We then performed whole-genome deep-sequencing of human- and matched mosquito-derived DENV samples on the Illumina platform and used a sensitive variant-caller to detect single nucleotide variants (SNVs) within each sample. >90% of SNVs were lost upon transition from human to mosquito, as well as from mosquito abdomen to salivary glands. Levels of viral diversity were maintained, however, by the regeneration of new SNVs at each stage of transmission. We further show that SNVs maintained across transmission stages were transmitted as a unit of two at maximum, suggesting the presence of numerous variant genomes carrying only one or two SNVs each. We also present evidence for differences in selection pressures between human and mosquito hosts, particularly on the structural and NS1 genes. This analysis provides insights into how population drops during transmission shape RNA virus genetic diversity, has direct implications for virus evolution, and illustrates the value of high-coverage, whole-genome next-generation sequencing for understanding viral intra-host genetic diversity.

Dengue viruses (DENV) cause debilitating and potentially life-threatening acute disease throughout the tropical world. While drug development efforts are underway, there are concerns that resistant strains will emerge rapidly. Indeed, antiviral drugs that target even conserved regions in other RNA viruses lose efficacy over time as the virus mutates. Here, we sought to determine if there are regions in the DENV genome that are not only evolutionarily conserved but genetically constrained in their ability to mutate and could hence serve as better antiviral targets. High-throughput sequencing of DENV-1 genome directly from twelve, paired dengue patients' sera and then passaging these sera into the two primary mosquito vectors showed consistent and distinct sequence changes during infection. In particular, two residues in the NS5 protein coding sequence appear to be specifically acquired during infection in Ae. aegypti but not Ae. albopictus. Importantly, we identified a region within the NS3 protein coding sequence that is refractory to mutation during human and mosquito infection. Collectively, these findings provide fresh insights into antiviral targets and could serve as an approach to defining evolutionarily constrained regions for therapeutic targeting in other RNA viruses.

The high throughput and cost-effectiveness afforded by short-read sequencing technologies, in principle, enable researchers to perform 16S rRNA profiling of complex microbial communities at unprecedented depth and resolution. Existing Illumina sequencing protocols are, however, limited by the fraction of the 16S rRNA gene that is interrogated and therefore limit the resolution and quality of the profiling. To address this, we present the design of a novel protocol for shotgun Illumina sequencing of the bacterial 16S rRNA gene, optimized to amplify more than 90% of sequences in the Greengenes database and with the ability to distinguish nearly twice as many species-level OTUs compared to existing protocols. Using several in silico and experimental datasets, we demonstrate that despite the presence of multiple variable and conserved regions, the resulting shotgun sequences can be used to accurately quantify the constituents of complex microbial communities. The reconstruction of a significant fraction of the 16S rRNA gene also enabled high precision (>90%) in species-level identification thereby opening up potential application of this approach for clinical microbial characterization.

Structural variations (SVs) contribute significantly to the variability of the human genome and extensive genomic rearrangements are a hallmark of cancer. While genomic DNA paired-end-tag (DNA-PET) sequencing is an attractive approach to identify genomic SVs, the current application of PET sequencing with short insert size DNA can be insufficient for the comprehensive mapping of SVs in low complexity and repeat-rich genomic regions. We employed a recently developed procedure to generate PET sequencing data using large DNA inserts of 10-20 kb and compared their characteristics with short insert (1 kb) libraries for their ability to identify SVs. Our results suggest that although short insert libraries bear an advantage in identifying small deletions, they do not provide significantly better breakpoint resolution. In contrast, large inserts are superior to short inserts in providing higher physical genome coverage for the same sequencing cost and achieve greater sensitivity, in practice, for the identification of several classes of SVs, such as copy number neutral and complex events. Furthermore, our results confirm that large insert libraries allow for the identification of SVs within repetitive sequences, which cannot be spanned by short inserts. This provides a key advantage in studying rearrangements in cancer, and we show how it can be used in a fusion-point-guided-concatenation algorithm to study focally amplified regions in cancer.

In April 2009, novel swine-origin influenza viruses (S-OIV) were identified in patients from Mexico and the United States. The viruses were genetically characterized as a novel influenza A (H1N1) strain originating in swine, and within a very short time the S-OIV strain spread across the globe via human-to-human contact.We conducted a comprehensive computational search of all available sequences of the surface proteins of H1N1 swine influenza isolates and found that a similar strain to S-OIV appeared in Thailand in 2000. The earlier isolates caused infections in pigs but only one sequenced human case, A/Thailand/271/2005 (H1N1).Differences between the Thai cases and S-OIV may help shed light on the ability of the current outbreak strain to spread rapidly among humans.

Numerous studies are currently underway to characterize the microbial communities inhabiting our world. These studies aim to dramatically expand our understanding of the microbial biosphere and, more importantly, hope to reveal the secrets of the complex symbiotic relationship between us and our commensal bacterial microflora. An important prerequisite for such discoveries are computational tools that are able to rapidly and accurately compare large datasets generated from complex bacterial communities to identify features that distinguish them.We present a statistical method for comparing clinical metagenomic samples from two treatment populations on the basis of count data (e.g. as obtained through sequencing) to detect differentially abundant features. Our method, Metastats, employs the false discovery rate to improve specificity in high-complexity environments, and separately handles sparsely-sampled features using Fisher's exact test. Under a variety of simulations, we show that Metastats performs well compared to previously used methods, and significantly outperforms other methods for features with sparse counts. We demonstrate the utility of our method on several datasets including a 16S rRNA survey of obese and lean human gut microbiomes, COG functional profiles of infant and mature gut microbiomes, and bacterial and viral metabolic subsystem data inferred from random sequencing of 85 metagenomes. The application of our method to the obesity dataset reveals differences between obese and lean subjects not reported in the original study. For the COG and subsystem datasets, we provide the first statistically rigorous assessment of the differences between these populations. The methods described in this paper are the first to address clinical metagenomic datasets comprising samples from multiple subjects. Our methods are robust across datasets of varied complexity and sampling level. While designed for metagenomic applications, our software can also be applied to digital gene expression studies (e.g. SAGE). A web server implementation of our methods and freely available source code can be found at http://metastats.cbcb.umd.edu/.