Ben Nichols

Bio: Ben Nichols is an academic researcher from Glasgow Royal Infirmary. The author has contributed to research in topics: Medicine & Microbiome. The author has an hindex of 8, co-authored 15 publications receiving 4002 citations. Previous affiliations of Ben Nichols include University of Glasgow.

VSEARCH: a versatile open source tool for metagenomics

Abstract: Background: VSEARCH is an open source and free of charge multithreaded 64-bit tool for processing and preparing metagenomics, genomics and population genomics nucleotide sequence data. It is designed as an alternative to the widely used USEARCH tool (Edgar, 2010) for which the source code is not publicly available, algorithm details are only rudimentarily described, and only a memory-confined 32-bit version is freely available for academic use. Methods: When searching nucleotide sequences, VSEARCH uses a fast heuristic based on words shared by the query and target sequences in order to quickly identify similar sequences, a similar strategy is probably used in USEARCH. VSEARCH then performs optimal global sequence alignment of the query against potential target sequences, using full dynamic programming instead of the seed-and-extend heuristic used by USEARCH. Pairwise alignments are computed in parallel using vectorisation and multiple threads. Results: VSEARCH includes most commands for analysing nucleotide sequences available in USEARCH version 7 and several of those available in USEARCH version 8, including searching (exact or based on global alignment), clustering by similarity (using length pre-sorting, abundance pre-sorting or a user-defined order), chimera detection (reference-based or de novo), dereplication (full length or prefix), pairwise alignment, reverse complementation, sorting, and subsampling. VSEARCH also includes commands for FASTQ file processing, i.e., format detection, filtering, read quality statistics, and merging of paired reads. Furthermore, VSEARCH extends functionality with several new commands and improvements, including shuffling, rereplication, masking of low-complexity sequences with the well-known DUST algorithm, a choice among different similarity definitions, and FASTQ file format conversion. VSEARCH is here shown to be more accurate than USEARCH when performing searching, clustering, chimera detection and subsampling, while on a par with USEARCH for paired-ends read merging. VSEARCH is slower than USEARCH when performing clustering and chimera detection, but significantly faster when performing paired-end reads merging and dereplication. VSEARCH is available at https://github.com/torognes/vsearch under either the BSD 2-clause license or the GNU General Public License version 3.0. Discussion: VSEARCH has been shown to be a fast, accurate and full-fledged alternative to USEARCH. A free and open-source versatile tool for sequence analysis is now available to the metagenomics community.

Metagenetic analysis of patterns of distribution and diversity of marine meiobenthic eukaryotes

Abstract: Aim Meiofaunal communities that inhabit the marine benthos offer unique opportunities to simultaneously study the macroecology of numerous phyla that exhibit different life-history strategies. Here, we ask: (1) if the macroecology of meiobenthic communities is explained mainly by dispersal constraints or by environmental conditions; and (2) if levels of meiofaunal diversity surpass existing estimates based on morphological taxonomy. Location UK and mainland European coast. Methods Next-generation sequencing techniques (NGS; Roche 454 FLX platform) using 18S nuclear small subunit ribosomal DNA (rDNA) gene. Pyrosequences were analysed using AmpliconNoise followed by chimera removal using Perseus. Results Rarefaction curves revealed that sampling saturation was only reached at 15% of sites, highlighting that the bulk of meiofaunal diversity is yet to be discovered. Overall, 1353 OTUs were recovered and assigned to 23 different phyla. The majority of sampled sites had c. 60–70 unique operational taxonomic units (OTUs) per site, indicating high levels of beta diversity. The environmental parameters that best explained community structure were seawater temperature, geographical distance and sediment size, but most of the variability (R 2 = 70%–80%) remains unexplained. Main conclusions High percentages of endemic OTUs suggest that meiobenthic community composition is partly niche-driven, as observed in larger organisms, but also shares macroecological features of microorganisms by showing high levels of cosmopolitanism (albeit on a much smaller scale). Meiobenthic communities exhibited patterns of isolation by distance as well as associations between niche, latitude and temperature, indicating that meiobenthic communities result from a combination of niche assembly and dispersal processes. Conversely, isolation-bydistance patterns were not identified in the featured protists, suggesting that animals and protists adhere to radically different macroecological processes, linked to life-history strategies.

The impact of food additives, artificial sweeteners and domestic hygiene products on the human gut microbiome and its fibre fermentation capacity

Abstract: This study investigated the effect of food additives, artificial sweeteners and domestic hygiene products on the gut microbiome and fibre fermentation capacity. Faecal samples from 13 healthy volunteers were fermented in batch cultures with food additives (maltodextrin, carboxymethyl cellulose, polysorbate-80, carrageenan-kappa, cinnamaldehyde, sodium benzoate, sodium sulphite, titanium dioxide), sweeteners (aspartame-based sweetener, sucralose, stevia) and domestic hygiene products (toothpaste and dishwashing detergent). Short-chain fatty acid production was measured with gas chromatography. Microbiome composition was characterised with 16S rRNA sequencing and quantitative polymerase chain reaction (qPCR). Acetic acid increased in the presence of maltodextrin and the aspartame-based sweetener and decreased with dishwashing detergent or sodium sulphite. Propionic acid increased with maltodextrin, aspartame-based sweetener, sodium sulphite and polysorbate-80 and butyrate decreased dramatically with cinnamaldehyde and dishwashing detergent. Branched-chain fatty acids decreased with maltodextrin, aspartame-based sweetener, cinnamaldehyde, sodium benzoate and dishwashing detergent. Microbiome Shannon α-diversity increased with stevia and decreased with dishwashing detergent and cinnamaldehyde. Sucralose, cinnamaldehyde, titanium dioxide, polysorbate-80 and dishwashing detergent shifted microbiome community structure; the effects were most profound with dishwashing detergent (R2 = 43.9%, p = 0.008) followed by cinnamaldehyde (R2 = 12.8%, p = 0.016). Addition of dishwashing detergent and cinnamaldehyde increased the abundance of operational taxonomic unit (OTUs) belonging to Escherichia/Shigella and Klebsiella and decreased members of Firmicutes, including OTUs of Faecalibacterium and Subdoligranulum. Addition of sucralose and carrageenan-kappa also increased the abundance of Escherichia/Shigella and sucralose, sodium sulphite and polysorbate-80 did likewise to Bilophila. Polysorbate-80 decreased the abundance of OTUs of Faecalibacterium and Subdoligranulum. Similar effects were observed with the concentration of major bacterial groups using qPCR. In addition, maltodextrin, aspartame-based sweetener and sodium benzoate promoted the growth of Bifidobacterium whereas sodium sulphite, carrageenan-kappa, polysorbate-80 and dishwashing detergent had an inhibitory effect. This study improves understanding of how additives might affect the gut microbiota composition and its fibre metabolic activity with many possible implications for human health.

VSEARCH: a versatile open source tool for metagenomics

Abstract: Background: VSEARCH is an open source and free of charge multithreaded 64-bit tool for processing and preparing metagenomics, genomics and population genomics nucleotide sequence data. It is designed as an alternative to the widely used USEARCH tool (Edgar, 2010) for which the source code is not publicly available, algorithm details are only rudimentarily described, and only a memory-confined 32-bit version is freely available for academic use. Methods: When searching nucleotide sequences, VSEARCH uses a fast heuristic based on words shared by the query and target sequences in order to quickly identify similar sequences, a similar strategy is probably used in USEARCH. VSEARCH then performs optimal global sequence alignment of the query against potential target sequences, using full dynamic programming instead of the seed-and-extend heuristic used by USEARCH. Pairwise alignments are computed in parallel using vectorisation and multiple threads. Results: VSEARCH includes most commands for analysing nucleotide sequences available in USEARCH version 7 and several of those available in USEARCH version 8, including searching (exact or based on global alignment), clustering by similarity (using length pre-sorting, abundance pre-sorting or a user-defined order), chimera detection (reference-based or de novo), dereplication (full length or prefix), pairwise alignment, reverse complementation, sorting, and subsampling. VSEARCH also includes commands for FASTQ file processing, i.e., format detection, filtering, read quality statistics, and merging of paired reads. Furthermore, VSEARCH extends functionality with several new commands and improvements, including shuffling, rereplication, masking of low-complexity sequences with the well-known DUST algorithm, a choice among different similarity definitions, and FASTQ file format conversion. VSEARCH is here shown to be more accurate than USEARCH when performing searching, clustering, chimera detection and subsampling, while on a par with USEARCH for paired-ends read merging. VSEARCH is slower than USEARCH when performing clustering and chimera detection, but significantly faster when performing paired-end reads merging and dereplication. VSEARCH is available at https://github.com/torognes/vsearch under either the BSD 2-clause license or the GNU General Public License version 3.0. Discussion: VSEARCH has been shown to be a fast, accurate and full-fledged alternative to USEARCH. A free and open-source versatile tool for sequence analysis is now available to the metagenomics community.

“Bioinformatics” 특집을 내면서

Abstract: BIOE 402. Medical Technology Assessment. 2 or 3 hours. Bioentrepreneur course. Assessment of medical technology in the context of commercialization. Objectives, competition, market share, funding, pricing, manufacturing, growth, and intellectual property; many issues unique to biomedical products. Course Information: 2 undergraduate hours. 3 graduate hours. Prerequisite(s): Junior standing or above and consent of the instructor.

Gut microbiome modulates response to anti–PD-1 immunotherapy in melanoma patients

Abstract: Preclinical mouse models suggest that the gut microbiome modulates tumor response to checkpoint blockade immunotherapy; however, this has not been well-characterized in human cancer patients. Here we examined the oral and gut microbiome of melanoma patients undergoing anti-programmed cell death 1 protein (PD-1) immunotherapy (n = 112). Significant differences were observed in the diversity and composition of the patient gut microbiome of responders versus nonresponders. Analysis of patient fecal microbiome samples (n = 43, 30 responders, 13 nonresponders) showed significantly higher alpha diversity (P < 0.01) and relative abundance of bacteria of the Ruminococcaceae family (P < 0.01) in responding patients. Metagenomic studies revealed functional differences in gut bacteria in responders, including enrichment of anabolic pathways. Immune profiling suggested enhanced systemic and antitumor immunity in responding patients with a favorable gut microbiome as well as in germ-free mice receiving fecal transplants from responding patients. Together, these data have important implications for the treatment of melanoma patients with immune checkpoint inhibitors.

Optimizing taxonomic classification of marker-gene amplicon sequences with QIIME 2’s q2-feature-classifier plugin

Abstract: Taxonomic classification of marker-gene sequences is an important step in microbiome analysis. We present q2-feature-classifier ( https://github.com/qiime2/q2-feature-classifier ), a QIIME 2 plugin containing several novel machine-learning and alignment-based methods for taxonomy classification. We evaluated and optimized several commonly used classification methods implemented in QIIME 1 (RDP, BLAST, UCLUST, and SortMeRNA) and several new methods implemented in QIIME 2 (a scikit-learn naive Bayes machine-learning classifier, and alignment-based taxonomy consensus methods based on VSEARCH, and BLAST+) for classification of bacterial 16S rRNA and fungal ITS marker-gene amplicon sequence data. The naive-Bayes, BLAST+-based, and VSEARCH-based classifiers implemented in QIIME 2 meet or exceed the species-level accuracy of other commonly used methods designed for classification of marker gene sequences that were evaluated in this work. These evaluations, based on 19 mock communities and error-free sequence simulations, including classification of simulated “novel” marker-gene sequences, are available in our extensible benchmarking framework, tax-credit ( https://github.com/caporaso-lab/tax-credit-data ). Our results illustrate the importance of parameter tuning for optimizing classifier performance, and we make recommendations regarding parameter choices for these classifiers under a range of standard operating conditions. q2-feature-classifier and tax-credit are both free, open-source, BSD-licensed packages available on GitHub.

A communal catalogue reveals Earth’s multiscale microbial diversity

Abstract: Our growing awareness of the microbial world’s importance and diversity contrasts starkly with our limited understanding of its fundamental structure. Despite recent advances in DNA sequencing, a lack of standardized protocols and common analytical frameworks impedes comparisons among studies, hindering the development of global inferences about microbial life on Earth. Here we present a meta-analysis of microbial community samples collected by hundreds of researchers for the Earth Microbiome Project. Coordinated protocols and new analytical methods, particularly the use of exact sequences instead of clustered operational taxonomic units, enable bacterial and archaeal ribosomal RNA gene sequences to be followed across multiple studies and allow us to explore patterns of diversity at an unprecedented scale. The result is both a reference database giving global context to DNA sequence data and a framework for incorporating data from future studies, fostering increasingly complete characterization of Earth’s microbial diversity.