A neoteric antibacterial ceria-silver nanozyme for abiotic surfaces.

Community-associated and hospital-acquired infections caused by bacteria continue to yield major global challenges to human health. Bacterial contamination on abiotic surfaces is largely spread via high-touch surfaces and contemporary standard disinfection practices show limited efficacy, resulting in unsatisfactory therapeutic outcomes. New strategies that offer non-specific and broad protection are urgently needed. Herein, we report our novel ceria-silver nanozyme engineered at a molar ratio of 5:1 and with a higher trivalent (Ce3+) surface fraction. Our results reveal potent levels of surface catalytic activity on both wet and dry surfaces, with rapid, and complete eradication of Pseudomonas aeruginosa, Staphylococcus aureus, and methicillin resistant S. aureus, in both planktonic and biofilm form. Preferential electrostatic adherence of anionic bacteria to the cationic nanozyme surface leads to a catastrophic loss in both aerobic and anaerobic respiration, DNA damage, osmodysregulation, and finally, programmed bacterial lysis. Our data reveal several unique mechanistic avenues of synergistic ceria-Ag efficacy. Ag potentially increases the presence of Ce3+ sites at the ceria-Ag interface, thereby facilitating the formation of harmful H2O2, followed by likely permeation across the cell wall. Further, a weakened Ag-induced Ce-O bond may drive electron transfer from the Ec band to O2, thereby further facilitating the selective reduction of O2 toward H2O2 formation. Ag destabilizes the surface adsorption of molecular H2O2, potentially leading to higher concentrations of free H2O2 adjacent to bacteria. To this end, our results show that H2O2 and/or NO/NO2-/NO3- are the key liberators of antibacterial activity, with a limited immediate role being offered by nanozyme-induced ROS including O2•- and OH•, and likely other light-activated radicals. A mini-pilot proof-of-concept study performed in a pediatric dental clinic setting confirms residual, and continual nanozyme antibacterial efficacy over a 28-day period. These findings open a new approach to alleviate infections caused by bacteria for use on high-touch hard surfaces.

Integrated de novo gene prediction and peptide assembly of metagenomic sequencing data.

Metagenomics is the study of all genomic content contained in given microbial communities. Metagenomic functional analysis aims to quantify protein families and reconstruct metabolic pathways from the metagenome. It plays a central role in understanding the interaction between the microbial community and its host or environment. De novo functional analysis, which allows the discovery of novel protein families, remains challenging for high-complexity communities. There are currently three main approaches for recovering novel genes or proteins: de novo nucleotide assembly, gene calling and peptide assembly. Unfortunately, their information dependency has been overlooked, and each has been formulated as an independent problem. In this work, we develop a sophisticated workflow called integrated Metagenomic Protein Predictor (iMPP), which leverages the information dependencies for better de novo functional analysis. iMPP contains three novel modules: a hybrid assembly graph generation module, a graph-based gene calling module, and a peptide assembly-based refinement module. iMPP significantly improved the existing gene calling sensitivity on unassembled metagenomic reads, achieving a 92-97% recall rate at a high precision level (>85%). iMPP further allowed for more sensitive and accurate peptide assembly, recovering more reference proteins and delivering more hypothetical protein sequences. The high performance of iMPP can provide a more comprehensive and unbiased view of the microbial communities under investigation. iMPP is freely available from https://github.com/Sirisha-t/iMPP.

Species-specific transcriptomic changes upon respiratory syncytial virus infection in cotton rats.

The cotton rat (Sigmodon) is the gold standard pre-clinical small animal model for respiratory viral pathogens, especially for respiratory syncytial virus (RSV). However, without a reference genome or a published transcriptome, studies requiring gene expression analysis in cotton rats are severely limited. The aims of this study were to generate a comprehensive transcriptome from multiple tissues of two species of cotton rats that are commonly used as animal models (Sigmodon fulviventer and Sigmodon hispidus), and to compare and contrast gene expression changes and immune responses to RSV infection between the two species. Transcriptomes were assembled from lung, spleen, kidney, heart, and intestines for each species with a contig N50 > 1600. Annotation of contigs generated nearly 120,000 gene annotations for each species. The transcriptomes of S. fulviventer and S. hispidus were then used to assess immune response to RSV infection. We identified 238 unique genes that are significantly differentially expressed, including several genes implicated in RSV infection (e.g., Mx2, I27L2, LY6E, Viperin, Keratin 6A, ISG15, CXCL10, CXCL11, IRF9) as well as novel genes that have not previously described in RSV research (LG3BP, SYWC, ABEC1, IIGP1, CREB1). This study presents two comprehensive transcriptome references as resources for future gene expression analysis studies in the cotton rat model, as well as provides gene sequences for mechanistic characterization of molecular pathways. Overall, our results provide generalizable insights into the effect of host genetics on host-virus interactions, as well as identify new host therapeutic targets for RSV treatment and prevention.

De Novo Genome Assembly Highlights the Role of Lineage-Specific Gene Duplications in the Evolution of Venom in Fea's Viper (Azemiops feae).

Despite the medical significance to humans and important ecological roles filled by vipers, few high-quality genomic resources exist for these snakes outside of a few genera of pitvipers. Here we sequence, assemble, and annotate the genome of Fea's Viper (Azemiops feae). This taxon is distributed in East Asia and belongs to a monotypic subfamily, sister to the pitvipers. The newly sequenced genome resulted in a 1.56 Gb assembly, a contig N50 of 1.59 Mb, with 97.6% of the genome assembly in contigs >50 Kb, and a BUSCO completeness of 92.4%. We found that A. feae venom is primarily composed of phospholipase A2 (PLA2) proteins expressed by genes that likely arose from lineage-specific PLA2 gene duplications. Additionally, we show that renin, an enzyme associated with blood pressure regulation in mammals and known from the venoms of two viper species including A. feae, is expressed in the venom gland at comparative levels to known toxins and is present in the venom proteome. The cooption of this gene as a toxin may be more widespread in viperids than currently known. To investigate the historical population demographics of A. feae, we performed coalescent-based analyses and determined that the effective population size has remained stable over the last 100 kyr. This suggests Quaternary glacial cycles likely had minimal influence on the demographic history of A. feae. This newly assembled genome will be an important resource for studying the genomic basis of phenotypic evolution and understanding the diversification of venom toxin gene families.

Maternal binge alcohol consumption leads to distinctive acute perturbations in embryonic cardiac gene expression profiles.

BACKGROUND: Excessive alcohol consumption during pregnancy is associated with high risk of congenital heart defects, but it is unclear how alcohol specifically affects heart development during the acute aftermath of a maternal binge drinking episode. We hypothesize that administration of a single maternal binge dose of alcohol to pregnant mice at embryonic day 9.5 (E9.5) causes perturbations in the expression patterns of specific genes in the developing heart in the acute period (1-3 days) following the binge episode. To test this hypothesis and identify strong candidate ethanol-sensitive target genes of interest, we adapted a mouse binge alcohol model that is associated with a high incidence of congenital heart defects as described below. METHODS/RESULTS: Pregnant mice were administered a single dose of alcohol (2.5 g/kg in saline) or control (saline alone) via oral gavage. To evaluate the impact of maternal binge alcohol on cardiac gene expression profiles, we isolated embryonic hearts from both groups (n = 5/group) at 24, 48, and 72 h post-gavage for transcriptomic analyses. RNA was extracted and evaluated using quantitative RNA-sequencing (RNA-Seq) methods. To identify a cohort of binge-altered cardiac genes, we set the threshold for change at >2.0-fold difference with adjusted p < 0.05 versus control.  RNA-Seq analysis of cardiac gene expression revealed that of the 17 genes that were altered within the first 48 h post-binge, with the largest category consisting of transcription factors (Alx1, Alx4, HoxB7, HoxD8, and Runx2), followed by signaling molecules (Adamts18, Dkk2, Rtl1, and Wnt7a). Furthermore, multiple comparative and pathway analyses suggested that several of the candidate genes identified through differential RNA-Seq analysis may interact through certain common pathways. To investigate this further, we performed gene-specific qPCR analyses for three representative candidate targets: Runx2, Wnt7a, and Mlxipl. Notably, only Wnt7a showed significantly (p < 0.05) decreased expression in response to maternal binge alcohol in the qPCR assays. CONCLUSIONS: These findings identify Wnt7a and a short list of potential other candidate genes and pathways for further study, which could provide mechanistic insights into how maternal binge alcohol consumption produces congenital cardiac malformations.

Variational Approximation-Based Model Selection for Microbial Network Inference.

Microbial associations are characterized by both direct and indirect interactions between the constituent taxa in a microbial community, and play an important role in determining the structure, organization, and function of the community. Microbial associations can be represented using a weighted graph (microbial network), whose nodes represent taxa and edges represent pairwise associations. A microbial network is typically inferred from a sample-taxa matrix that is obtained by sequencing multiple biological samples and identifying the taxa counts in each sample. However, it is known that microbial associations are impacted by environmental and/or host factors. Thus, a sample-taxa matrix generated in a microbiome study involving a wide range of values for the environmental and/or clinical metadata variables may in fact be associated with more than one microbial network. In this study, we consider the problem of inferring multiple microbial networks from a given sample-taxa count matrix. Each sample is a count vector assumed to be generated by a mixture model consisting of component distributions that are multivariate Poisson log-normal. We present a variational expectation maximization algorithm for the model selection problem to infer the correct number of components of this mixture model. Our approach involves reframing the mixture model as a latent variable model, treating only the mixing coefficients as parameters, and subsequently approximating the marginal likelihood using an evidence lower bound framework. Our algorithm is evaluated on a large simulated dataset generated using a collection of different graph structures (band, hub, cluster, random, and scale-free).

Metatranscriptomics to characterize respiratory virome, microbiome, and host response directly from clinical samples.

We developed a metatranscriptomics method that can simultaneously capture the respiratory virome, microbiome, and host response directly from low biomass samples. Using nasal swab samples, we capture RNA virome with sufficient sequencing depth required to assemble complete genomes. We find a surprisingly high frequency of respiratory syncytial virus (RSV) and coronavirus (CoV) in healthy children, and a high frequency of RSV-A and RSV-B co-detections in children with symptomatic RSV. In addition, we have identified commensal and pathogenic bacteria and fungi at the species level. Functional analysis revealed that H. influenzae was highly active in symptomatic RSV subjects. The host nasal transcriptome reveled upregulation of the innate immune system, anti-viral response and inflammasome pathway, and downregulation of fatty acid pathways in children with symptomatic RSV. Overall, we demonstrate that our method is broadly applicable to infer the transcriptome landscape of an infected system, surveil respiratory infections, and to sequence RNA viruses directly from clinical samples.

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.

Bacterial community structure alterations within the colorectal cancer gut microbiome.

BACKGROUND: Colorectal cancer is a leading cause of cancer-related deaths worldwide. The human gut microbiome has become an active area of research for understanding the initiation, progression, and treatment of colorectal cancer. Despite multiple studies having found significant alterations in the carriage of specific bacteria within the gut microbiome of colorectal cancer patients, no single bacterium has been unequivocally connected to all cases. Whether alterations in species carriages are the cause or outcome of cancer formation is still unclear, but what is clear is that focus should be placed on understanding changes to the bacterial community structure within the cancer-associated gut microbiome. RESULTS: By applying a novel set of analyses on 252 previously published whole-genome shotgun sequenced fecal samples from healthy and late-stage colorectal cancer subjects, we identify taxonomic, functional, and structural changes within the cancer-associated human gut microbiome. Bacterial association networks constructed from these data exhibited widespread differences in the underlying bacterial community structure between healthy and colorectal cancer associated gut microbiomes. Within the cancer-associated ecosystem, bacterial species were found to form associations with other species that are taxonomically and functionally dissimilar to themselves, as well as form modules functionally geared towards potential changes in the tumor-associated ecosystem. Bacterial community profiling of these samples revealed a significant increase in species diversity within the cancer-associated gut microbiome, and an elevated relative abundance of species classified as originating from the oral microbiome including, but not limited to, Fusobacterium nucleatum, Peptostreptococcus stomatis, Gemella morbillorum, and Parvimonas micra. Differential abundance analyses of community functional capabilities revealed an elevation in functions linked to virulence factors and peptide degradation, and a reduction in functions involved in amino-acid biosynthesis within the colorectal cancer gut microbiome. CONCLUSIONS: We utilize whole-genome shotgun sequenced fecal samples provided from a large cohort of late-stage colorectal cancer and healthy subjects to identify a number of potentially important taxonomic, functional, and structural alterations occurring within the colorectal cancer associated gut microbiome. Our analyses indicate that the cancer-associated ecosystem influences bacterial partner selection in the native microbiota, and we highlight specific oral bacteria and their associations as potentially relevant towards aiding tumor progression.

Microbial community structure and composition is associated with host species and sex in Sigmodon cotton rats.

BACKGROUND: The cotton rat (genus Sigmodon) is an essential small animal model for the study of human infectious disease and viral therapeutic development. However, the impact of the host microbiome on infection outcomes has not been explored in this model, partly due to the lack of a comprehensive characterization of microbial communities across different cotton rat species. Understanding the dynamics of their microbiome could significantly help to better understand its role when modeling viral infections in this animal model. RESULTS: We examined the bacterial communities of the gut and three external sites (skin, ear, and nose) of two inbred species of cotton rats commonly used in research (S. hispidus and S. fulviventer) by using 16S rRNA gene sequencing, constituting the first comprehensive characterization of the cotton rat microbiome. We showed that S. fulviventer maintained higher alpha diversity and richness than S. hispidus at external sites (skin, ear, nose), but there were no differentially abundant genera. However, S. fulviventer and S. hispidus had distinct fecal microbiomes composed of several significantly differentially abundant genera. Whole metagenomic shotgun sequencing of fecal samples identified species-level differences between S. hispidus and S. fulviventer, as well as different metabolic pathway functions as a result of differential host microbiome contributions. Furthermore, the microbiome composition of the external sites showed significant sex-based differences while fecal communities were not largely different. CONCLUSIONS: Our study shows that host genetic background potentially exerts homeostatic pressures, resulting in distinct microbiomes for two different inbred cotton rat species. Because of the numerous studies that have uncovered strong relationships between host microbiome, viral infection outcomes, and immune responses, our findings represent a strong contribution for understanding the impact of different microbial communities on viral pathogenesis. Furthermore, we provide novel cotton rat microbiome data as a springboard to uncover the full therapeutic potential of the microbiome against viral infections.

Pulmonary Microbiome of Patients Receiving Mechanical Ventilation: Changes Over Time.

BACKGROUND: Interest in the pulmonary microbiome is growing, particularly in patients undergoing mechanical ventilation. OBJECTIVES: To explore the pulmonary microbiome over time in patients undergoing prolonged mechanical ventilation and to evaluate the effect of an oral suctioning intervention on the microbiome. METHODS: This descriptive subanalysis from a clinical trial involved a random sample of 16 participants (7 intervention, 9 control) who received mechanical ventilation for at least 5 days. Five paired oral and tracheal specimens were evaluated for each participant over time. Bacterial DNA from the paired specimens was evaluated using 16S rRNA gene sequencing. Bacterial taxonomy composition, α-diversity (Shannon index), and ß-diversity (Morisita-Horn index) were calculated and compared within and between participants. RESULTS: Participants were predominantly male (69%) and White (63%), with a mean age of 58 years, and underwent mechanical ventilation for a mean of 9.36 days. Abundant bacterial taxa included Prevotella, Staphylococcus, Streptococcus, Stenotrophomonas, and Veillonella. Mean tracheal α-diversity decreased over time for the total group (P = .002) and the control group (P = .02). ß-Diversity was lower (P = .04) in the control group (1.905) than in the intervention group (2.607). CONCLUSIONS: Prolonged mechanical ventilation was associated with changes in the pulmonary microbiome, with the control group having less diversity. The oral suctioning intervention may have reduced oral-tracheal bacterial transmission.

Bacterial associations in the healthy human gut microbiome across populations.

In a microbial community, associations between constituent members play an important role in determining the overall structure and function of the community. The human gut microbiome is believed to play an integral role in host health and disease. To understand the nature of bacterial associations at the species level in healthy human gut microbiomes, we analyzed previously published collections of whole-genome shotgun sequence data, totaling over 1.6 Tbp, generated from 606 fecal samples obtained from four different healthy human populations. Using a Random Forest Classifier, we identified 202 signature bacterial species that were prevalent in these populations and whose relative abundances could be used to accurately distinguish between the populations. Bacterial association networks were constructed with these signature species using an approach based on the graphical lasso. Network analysis revealed conserved bacterial associations across populations and a dominance of positive associations over negative associations, with this dominance being driven by associations between species that are closely related either taxonomically or functionally. Bacterial species that form network modules, and species that constitute hubs and bottlenecks, were also identified. Functional analysis using protein families suggests that much of the taxonomic variation across human populations does not foment substantial functional or structural differences.

Peroxidized Linoleic Acid, 13-HPODE, Alters Gene Expression Profile in Intestinal Epithelial Cells.

Lipid peroxides (LOOHs) abound in processed food and have been implicated in the pathology of diverse diseases including gut, cardiovascular, and cancer diseases. Recently, RNA Sequencing (RNA-seq) has been widely used to profile gene expression. To characterize gene expression and pathway dysregulation upon exposure to peroxidized linoleic acid, we incubated intestinal epithelial cells (Caco-2) with 100 µM of 13-hydroperoxyoctadecadienoic acid (13-HPODE) or linoleic acid (LA) for 24 h. Total RNA was extracted for library preparation and Illumina HiSeq sequencing. We identified 3094 differentially expressed genes (DEGs) in 13-HPODE-treated cells and 2862 DEGs in LA-treated cells relative to untreated cells. We show that 13-HPODE enhanced lipid metabolic pathways, including steroid hormone biosynthesis, PPAR signaling, and bile secretion, which alter lipid uptake and transport. 13-HPODE and LA treatments promoted detoxification mechanisms including cytochrome-P450. Conversely, both treatments suppressed oxidative phosphorylation. We also show that both treatments may promote absorptive cell differentiation and reduce proliferation by suppressing pathways involved in the cell cycle, DNA synthesis/repair and ribosomes, and enhancing focal adhesion. A qRT-PCR analysis of representative DEGs validated the RNA-seq analysis. This study provides insights into mechanisms by which 13-HPODE alters cellular processes and its possible involvement in mitochondrial dysfunction-related disorders and proposes potential therapeutic strategies to treat LOOH-related pathologies.

Identification of Nasal Gammaproteobacteria with Potent Activity against Staphylococcus aureus: Novel Insights into the "Noncarrier" State.

Staphylococcus aureus nasal carriage provides the bacterial reservoir for opportunistic infection. In comparing the nasal microbiomes of culture-defined persistent S. aureus carriers versus noncarriers, we detected S. aureus DNA in all noses, including those with an established history of S. aureus negativity based on culture. Colonization with Gammaproteobacteria, including Klebsiella aerogenes, Citrobacter koseri, Moraxella lincolnii, and select Acinetobacter spp., was associated with S. aureus noncarriage. We next developed physiological competition assays for testing anti-S. aureus activity of isolated nasal species, utilizing medium modeling the nutrient-limited fluid of the nasal mucosa, polarized primary nasal epithelia, and nasal secretions. K. aerogenes from the nose of an S. aureus noncarrier demonstrated >99% inhibition of S. aureus recovery in all assays, even when S. aureus was coincubated in 9-fold excess. Secreted S. aureus inhibitory proteins from K. aerogenes and M. lincolnii were heat-stable and <30 kDa, fitting the profile of antimicrobial peptides. C. koseri, Acinetobacter haemolyticus, Acinetobacter junii, and Acinetobacter schindleri inhibited S. aureus recovery on nasal epithelia in a contact-dependent manner, while several other species either had no effect or promoted S. aureus growth. Collectively, this project is one of the first to identify resident nasal microbial species that impede S. aureus survival, and it implies that detectable nasal S. aureus results from shifts in microbial community composition.IMPORTANCE Nasal carriage of Staphylococcus aureus is a risk factor for infection, but it is not yet understood why some individuals carry nasal S. aureus persistently, intermittently, or seemingly not at all when tested via culture methods. This study compared the nasal microbiomes of established S. aureus carriers and noncarriers, identified species associated with noncarriage, and tested them for anti-S. aureus activity using assays developed to model the nutrient-limited nasal mucosa. We determined that all nostril swabs contain S. aureus DNA, even swabs from hosts considered to be long-term noncarriers. Select members of the Gammaproteobacteria class were more prevalent in noncarrier than carrier nostrils and demonstrated potent activity against multiple strains of S. aureus The results described here provide a better understanding of how the nasal microbiome controls S. aureus growth and viability and may be useful in the design of improved S. aureus decolonization strategies.

Evaluation of the upper airway microbiome and immune response with nasal epithelial lining fluid absorption and nasal washes.

Despite being commonly used to collect upper airway epithelial lining fluid, nasal washes are poorly reproducible, not suitable for serial sampling, and limited by a dilution effect. In contrast, nasal filters lack these limitations and are an attractive alternative. To examine whether nasal filters are superior to nasal washes as a sampling method for the characterization of the upper airway microbiome and immune response, we collected paired nasal filters and washes from a group of 40 healthy children and adults. To characterize the upper airway microbiome, we used 16S ribosomal RNA and shotgun metagenomic sequencing. To characterize the immune response, we measured total protein using a BCA assay and 53 immune mediators using multiplex magnetic bead-based assays. We conducted statistical analyses to compare common microbial ecology indices and immune-mediator median fluorescence intensities (MFIs) between sample types. In general, nasal filters were more likely to pass quality control in both children and adults. There were no significant differences in microbiome community richness, α-diversity, or structure between pediatric samples types; however, these were all highly dissimilar between adult sample types. In addition, there were significant differences in the abundance of amplicon sequence variants between sample types in children and adults. In adults, total proteins were significantly higher in nasal filters than nasal washes; consequently, the immune-mediator MFIs were not well detected in nasal washes. Based on better quality control sequencing metrics and higher immunoassay sensitivity, our results suggest that nasal filters are a superior sampling method to characterize the upper airway microbiome and immune response in both children and adults.

Global ecotypes in the ubiquitous marine clade SAR86.

SAR86 is an abundant and ubiquitous heterotroph in the surface ocean that plays a central role in the function of marine ecosystems. We hypothesized that despite its ubiquity, different SAR86 subgroups may be endemic to specific ocean regions and functionally specialized for unique marine environments. However, the global biogeographical distributions of SAR86 genes, and the manner in which these distributions correlate with marine environments, have not been investigated. We quantified SAR86 gene content across globally distributed metagenomic samples and modeled these gene distributions as a function of 51 environmental variables. We identified five distinct clusters of genes within the SAR86 pangenome, each with a unique geographic distribution associated with specific environmental characteristics. Gene clusters are characterized by the strong taxonomic enrichment of distinct SAR86 genomes and partial assemblies, as well as differential enrichment of certain functional groups, suggesting differing functional and ecological roles of SAR86 ecotypes. We then leveraged our models and high-resolution, remote sensing-derived environmental data to predict the distributions of SAR86 gene clusters across the world's oceans, creating global maps of SAR86 ecotype distributions. Our results reveal that SAR86 exhibits previously unknown, complex biogeography, and provide a framework for exploring geographic distributions of genetic diversity from other microbial clades.

Learning a mixture of microbial networks using minorization-maximization.

MOTIVATION: The interactions among the constituent members of a microbial community play a major role in determining the overall behavior of the community and the abundance levels of its members. These interactions can be modeled using a network whose nodes represent microbial taxa and edges represent pairwise interactions. A microbial network is typically constructed from a sample-taxa count matrix that is obtained by sequencing multiple biological samples and identifying taxa counts. From large-scale microbiome studies, it is evident that microbial community compositions and interactions are impacted by environmental and/or host factors. Thus, it is not unreasonable to expect that a sample-taxa matrix generated as part of a large study involving multiple environmental or clinical parameters can be associated with more than one microbial network. However, to our knowledge, microbial network inference methods proposed thus far assume that the sample-taxa matrix is associated with a single network. RESULTS: We present a mixture model framework to address the scenario when the sample-taxa matrix is associated with K microbial networks. This count matrix is modeled using a mixture of K Multivariate Poisson Log-Normal distributions and parameters are estimated using a maximum likelihood framework. Our parameter estimation algorithm is based on the minorization-maximization principle combined with gradient ascent and block updates. Synthetic datasets were generated to assess the performance of our approach on absolute count data, compositional data and normalized data. We also addressed the recovery of sparse networks based on an l1-penalty model. AVAILABILITY AND IMPLEMENTATION: MixMPLN is implemented in R and is freely available at https://github.com/sahatava/MixMPLN. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

GRASP2: fast and memory-efficient gene-centric assembly and homolog search for metagenomic sequencing data.

BACKGROUND: A crucial task in metagenomic analysis is to annotate the function and taxonomy of the sequencing reads generated from a microbiome sample. In general, the reads can either be assembled into contigs and searched against reference databases, or individually searched without assembly. The first approach may suffer from fragmentary and incomplete assembly, while the second is hampered by the reduced functional signal contained in the short reads. To tackle these issues, we have previously developed GRASP (Guided Reference-based Assembly of Short Peptides), which accepts a reference protein sequence as input and aims to assemble its homologs from a database containing fragmentary protein sequences. In addition to a gene-centric assembly tool, GRASP also serves as a homolog search tool when using the assembled protein sequences as templates to recruit reads. GRASP has significantly improved recall rate (60-80% vs. 30-40%) compared to other homolog search tools such as BLAST. However, GRASP is both time- and space-consuming. Subsequently, we developed GRASPx, which is 30X faster than GRASP. Here, we present a completely redesigned algorithm, GRASP2, for this computational problem. RESULTS: GRASP2 utilizes Burrows-Wheeler Transformation (BWT) and FM-index to perform assembly graph generation, and reduces the search space by employing a fast ungapped alignment strategy as a filter. GRASP2 also explicitly generates candidate paths prior to alignment, which effectively uncouples the iterative access of the assembly graph and alignment matrix. This strategy makes the execution of the program more efficient under current computer architecture, and contributes to GRASP2's speedup. GRASP2 is 8-fold faster than GRASPx (and 250-fold faster than GRASP) and uses 8-fold less memory while maintaining the original high recall rate of GRASP. GRASP2 reaches ~ 80% recall rate compared to that of ~ 40% generated by BLAST, both at a high precision level (> 95%). With such a high performance, GRASP2 is only ~3X slower than BLASTP. CONCLUSION: GRASP2 is a high-performance gene-centric and homolog search tool with significant speedup compared to its predecessors, which makes GRASP2 a useful tool for metagenomics data analysis, GRASP2 is implemented in C++ and is freely available from http://www.sourceforge.net/projects/grasp2 .

Gut microbiota dependent anti-tumor immunity restricts melanoma growth in Rnf5-/- mice.

Accumulating evidence points to an important role for the gut microbiome in anti-tumor immunity. Here, we show that altered intestinal microbiota contributes to anti-tumor immunity, limiting tumor expansion. Mice lacking the ubiquitin ligase RNF5 exhibit attenuated activation of the unfolded protein response (UPR) components, which coincides with increased expression of inflammasome components, recruitment and activation of dendritic cells and reduced expression of antimicrobial peptides in intestinal epithelial cells. Reduced UPR expression is also seen in murine and human melanoma tumor specimens that responded to immune checkpoint therapy. Co-housing of Rnf5-/- and WT mice abolishes the anti-tumor immunity and tumor inhibition phenotype, whereas transfer of 11 bacterial strains, including B. rodentium, enriched in Rnf5-/- mice, establishes anti-tumor immunity and restricts melanoma growth in germ-free WT mice. Altered UPR signaling, exemplified in Rnf5-/- mice, coincides with altered gut microbiota composition and anti-tumor immunity to control melanoma growth.