Journal: The ISME Journal

Article Title: Resolution of habitat-associated ecogenomic signatures in bacteriophage genomes and application to microbial source tracking

doi: 10.1038/s41396-017-0015-7

Figure Lengend Snippet: Unsupervised ordination of metagenomic data sets based on phage ecogenomic signatures. Non-metric multidimensional scaling (nMDS) was used to ordinate individual metagenomic data sets based on the relative abundance profiles of individual ORFs from either ɸB124-14 or ɸSYN5. The strength and significance of separation between groups of metagenomes with related environmental origins was evaluated using ANOSIM. To reduce the noise and increase stringency, only metagenomes with representation of two or more distinct phage ORFs were included in this analysis. a , b , d , e nMDS ordination of all metagenomes (all data sets), or exclusively viral metagenomes (viromes only), based on ɸB124-14 or ɸSYN5 ORF relative abundance profiles. Filled ellipses show standard deviation of dispersion of each group relative to the group centroid. For nMDS based on ɸSYN5 relative abundance profiles, no data sets from human gut virome assemblies, human oral cavity or human body sites met the minimum criteria for inclusion. c , f ANOSIM analysis of differences between groups of metagenomes used in nMDS. Charts show the ANOSIM R statistic for each comparison relative to the unassembled human gut viral data sets. An increasing strength of separation between groups is indicated as the R statistic approaches 1 (total separation). Symbols above bars indicate statistical significance of observed separation between groups: ** P ≤ 0.001, * P ≤ 0.05. For ɸSYN5 analyses, groups where no data sets met the threshold criteria for representation of a minimum of two distinct ORFs, were not included in nMDS or ANOSIM and indicated as 'failed detection threshold' in f . Human gut viromes, bovine viromes, porcine viromes, env viromes—unassembled viral metagenomes derived, respectively, from the human, bovine and porcine gut, or of non-host-associated environmental origin; human gut viromes (assem)—assemblies of human gut viral data sets; human gut whole, NH gut—whole community data sets derived from human or non-human gut, respectively; body, oral—whole community metagenomes from various human body sites or the oral cavity, respectively. env whole—whole community metagenomes non-host-associated environmental origin. Details of data sets in each group are provided in Supplementary Table

Article Snippet: Graphical representations of nMDS ordinations were produced using Vegan ordiplot functions in R. ANOSIM data were visualised using GraphPad Prism 6.0 for OS X.

Techniques: Standard Deviation, Dispersion, Comparison, Derivative Assay

Journal: The ISME Journal

Article Title: Resolution of habitat-associated ecogenomic signatures in bacteriophage genomes and application to microbial source tracking

doi: 10.1038/s41396-017-0015-7

Figure Lengend Snippet: Detection of human gut-associated ecogenomic signals in simulated 'polluted' environmental data sets. The potential for the ɸB124-14 ecogenomic signal to identify human faecal pollution in environmental data sets was explored by simulating pollution of selected environmental viromes. This was achieved by combining average human gut virome ɸB124-14, or ɸSYN5 relative abundance profiles, with those of selected environmental viromes. Human gut-associated profiles were combined at 'strengths' ranging from 100 to 0.01% of human gut virome average, with profiles of viromes from the Bay of British Columbia, Sargasso Sea, Gulf of Mexico, Tampa Bay and Reclaimed Water. Relationships between groups of 'uncontaminated' and 'polluted' metagenomes were explored using nMDS and ANOSIM as for Fig. . a , c nMDS ordination of uncontaminated metagenomes and those modified to include either ɸB124-14 or ɸSYN5 human gut virome profiles. Filled ellipses show standard deviation of dispersion of each group relative to the group centroid. Black ellipse denotes groups of 'polluted' environmental data sets, with 'strength' (100–0.01%) of human gut signal added. b , d ANOSIM analysis of the differences between groups of metagenomes used in nMDS ordination. Charts show the ANOSIM R statistic for each uncontaminated group of metagenomes compared with data sets modified to simulate different levels of human faecal pollution. An increasing strength of separation between groups is indicated as the R statistic approaches 1 (total separation). Open symbols indicate no significant separation from the polluted data set compared, while closed symbols indicate significant separation ( P ≤ 0.05). Human gut viromes, bovine viromes, porcine viromes, env viromes—unassembled viral metagenomes derived, respectively, from the human, bovine and porcine gut, or of non-host-associated environmental origin; env whole—whole community metagenomes non-host-associated environmental origin. Details of data sets in each group are provided in Supplementary Table

Article Snippet: Graphical representations of nMDS ordinations were produced using Vegan ordiplot functions in R. ANOSIM data were visualised using GraphPad Prism 6.0 for OS X.

Techniques: Modification, Standard Deviation, Dispersion, Derivative Assay

Journal: The ISME Journal

Article Title: Resolution of habitat-associated ecogenomic signatures in bacteriophage genomes and application to microbial source tracking

doi: 10.1038/s41396-017-0015-7

Figure Lengend Snippet: Simulation and modelling of virome-based source tracking using ɸB124-14 ecogenomic signatures. To evaluate the potential for the ɸB124-14 ecogenomic signature to be used in MST, we undertook more extensive Monte Carlo-based simulations of pollution using randomly permuted and polluted environmental viromes, and specific detection of human pollution using ɸB124-14 ORF relative abundance profiles. a nMDS and ANOSIM analysis of uncontaminated and 'polluted' permutations of environmental viral metagenomes. Symbol shape for polluted data sets (human, bovine or porcine) represents the strength of contamination as indicated by the associated key. ANOSIM shows the separation of groups of data sets with varying ranges of human or animal contamination, from uncontaminated environmental viromes (** P = 0.001). ENV U —uncontaminated environmental virome permutations; ENV HGV —environmental virome permutations contaminated by human gut ecogenomic signature; ENV BOV —environmental virome permutations contaminated by bovine gut ecogenomic signature; ENV PORC —environmental virome permutations contaminated by porcine gut ecogenomic signature; b ROC curves were constructed from randomly permuted and polluted data sets displayed in a , based on relative abundance profiles from all ɸB124-14 ORFS, or a subset of ORFS exhibiting significantly different mean relative abundance in human gut viromes than other data sets (see Fig. ). Subset 1 ORFS = 5, 16, 18, 20, 21, 22, 23, 25, 34, 36, 43, 44, 59, 61 and 67; subset 2 ORFS = 16, 34 and 56. The area under curve (AUC) for each ROC curve indicate the diagnostic potential for cumulative relative abundance of each ORF combination to distinguish different groups of data sets, with values approaching 0.5 indicating little or no diagnostic power. All AUC were statistically significant at P ≤ 0.002. c Histograms show the proportion of data sets of each type ( ENV U ; ENV HGV ; ENV BOV ; ENV PORC ) accurately identified by a two-step classification approach using threshold values indicative of either pollution in general (step 1) or human pollution more specifically (Step 2), selected based on sensitivity and specificity values generated by ROC analyses (a minimum sensitivity of 0.91). This pipeline was evaluated using threshold values for binning derived from either subset 1 ORFS, subset 2 ORFS or a combination in which subset 1 values were applied to step 1, and subset 2 values were applied to step 2. **** P < 0.0001. Error bars show standard error of the mean from 100 iterations with 100 new randomly permuted and polluted data sets of each type per iteration

Article Snippet: Graphical representations of nMDS ordinations were produced using Vegan ordiplot functions in R. ANOSIM data were visualised using GraphPad Prism 6.0 for OS X.

Techniques: Construct, Diagnostic Assay, Generated, Derivative Assay

Journal: bioRxiv

Article Title: Adult organotypic brain slice cultures recapitulate extracellular matrix remodelling in haemorrhagic stroke

doi: 10.1101/2025.07.15.665021

Figure Lengend Snippet: RT-qPCR validation of RNA-sequencing. Top 6 downregulated (lower expression in blood-exposed samples) and top 6 upregulated (higher expression in blood-exposed samples). All statistical analyses were performed with unpaired t-tests. ns = not significant, ns = not significant, * P < 0.05, ** P < 0.01, *** P < 0.001, **** P < 0.0001, N = 3, α = 0.05.

Article Snippet: All visualisation of RNA- sequencing data was performed using GraphPad Prism 10.3.

Techniques: Quantitative RT-PCR, Biomarker Discovery, RNA Sequencing, Expressing