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Williams, R. B. H.

Publications and source records attributed to Williams, R. B. H..

13 recordsLinked to original sources
bioRxiv2023

Exploring the genetic architecture of ecophysiological traits in microbial ecology using statistical analysis of the properties of protein sequences: application to the glycogen accumulating organism (GAO) phenotype

Nearly 50 years ago, King and Wilson introduced a key distinction between two types of genetic variation-named structural and regulatory variation-for exploring the molecular basis for phenotypic traits. Structural variation is genetic variation that will influence gene product structure via changes in coding sequence, whereas regulatory variation will influence the control of gene product expression. Here we repurpose these concepts to study the molecular basis of eco-physiological traits observed in microbial ecology, focusing on a specialized glycogen accumulating phenotype, known to be exhibited by a phylogenetically diverse group of microbes. We analyse the statistical properties of the protein sequence of the 1,4--glucan branching enzyme (glgB), a key enzyme responsible for formation of glycogen from linear glucans. We show that the glgB proteins in a subgroup of these organisms show unusual statistical properties of protein sequence length, sequence similarity and patterning of functional domains, compared to organisms that do not exhibit this phenotype. These findings suggest a role for structural genetic variation in determining this phenotype in some species. Our analysis holds implications for dissecting the genetic/genomic architecture of complex traits exhibited by microbial communities and also provides a complementary framework to presence-absence level analyses that are ubiquitous in microbial ecology.

genomics↗
bioRxiv2022

Machine-learning based detection of adventitious microbes in T-cell therapy cultures using long read sequencing

Assuring that cell therapy products are safe before releasing them for use in patients is critical. Currently, compendial sterility testing for bacteria and fungi can take 7-14 days. The goal of this work was to develop a rapid untargeted approach for the sensitive detection of microbial contaminants at low abundance from low volume samples during the manufacturing process of cell therapies. We developed a long-read sequencing methodology using Oxford Nanopore Technologies MinION platform with 16S and 18S amplicon sequencing to detect USP<71> organisms and other microbial species. Reads are classified metagenomically to predict the microbial species. We used an extreme gradient boosting machine learning algorithm (XGBoost) to first assess if a sample is contaminated and second, determine whether the predicted contaminant is correctly classified or misclassified. The model was used to make a final decision on the sterility status of the input sample. An optimised experimental and bioinformatics pipeline starting from spiked species through to sequenced reads allowed for the detection of microbial samples at 10 CFU / mL using metagenomic classification. Machine learning can be coupled with long read sequencing to detect and identify sample sterility status and microbial species present in T-cell cultures, including the USP<71> organisms to 10 CFU / mL. ImportanceThis research presents a novel method for rapidly and accurately detecting microbial contaminants in cell therapy products, which is essential for ensuring patient safety. Traditional testing methods are time-consuming, taking 7-14 days, while our approach can significantly reduce this time. By combining advanced long read Nanopore sequencing techniques and machine learning, we can effectively identify the presence and types of microbial contaminants at low abundance levels. This breakthrough has the potential to improve the safety and efficiency of cell therapy manufacturing, leading to better patient outcomes and a more streamlined production process.

bioinformatics↗
bioRxiv2021

Recovery of high quality metagenome-assembled genomes from full-scale activated sludge microbial communities in a tropical climate using longitudinal metagenome sampling

Analysis of metagenome data based on the recovery of draft genomes (so called metagenome-assembled genomes, or MAG) have assumed an increasingly central role in microbiome research in recent years. Microbial communities underpinning the operation of wastewater treatment plants are particularly challenging targets for MAG analysis due to their high ecological complexity, and remain important, albeit understudied, microbial communities that play a key role in mediating interactions between human and natural ecosystems. In this paper, we consider strategies for recovery of MAG sequence from time series metagenome surveys of full-scale activated sludge microbial communities. We generate MAG catalogues from this set of data using several different strategies, including the use of multiple individual sample assemblies, two variations on multi-sample co-assembly and a recently published MAG recovery workflow using deep learning. We obtain a total of just under 9,100 draft genomes, which collapse to around 3,100 non-redundant genomic clusters. We examine the strengths and weaknesses of these approaches in relation to MAG yield and quality, showing the co-assembly offers clear advantages over single-sample assembly. Around 1000 MAGs were candidates for being considered high quality, based on single-copy marker gene occurrence statistics, however only 58 MAG formally meet the MIMAG criteria for being high quality draft genomes. These findings carry broader implications for performing genome-resolved metagenomics on highly complex communities, the design and implementation of genome recoverability strategies, MAG decontamination and the search for better binning methodology.

genomics↗
bioRxiv2021

Metagenomics and Metatranscriptomics Reveal Pathway of 3-Chloroaniline Degradation in Wastewater Reactors

Biological wastewater treatment systems are often affected by major shifts in influent quality, including the input of various toxic chemicals. Yet the mechanisms underlying adaptation of activated sludge process performance when challenged with a sustained toxin input are rarely studied in a controlled and replicated experimental setting. Three replicate bench-scale bioreactors were subjected to a chemical disturbance in the form of 3-chloroaniline (3-CA) over 132 days, after an acclimation period of 58 days, while three control reactors received no 3-CA input. Nitrification was initially affected by 3-CA but the microbial communities in all three treatment reactors adapted to biologically degrade 3-CA within three weeks of the experiment, resulting in partial nitrification recovery. Combining process and microbial community data from amplicon sequencing with potential functions gleaned from assembled metagenomics and metatranscriptomics data, two putative degradation pathways for 3-CA were identified. The first pathway proceeds via a phenol monooxygenase followed by ortho-cleavage of the aromatic ring, and the second one involves a benzoate dioxygenase and subsequent meta-cleavage of the aromatic ring. The genera Gemmatimonas, OLB8, and Taibaiella correlated significantly with 3-CA degradation. Metagenome-assembled genome data also showed the genus OLB8 to be differentially enriched in treatment reactors, making it a strong candidate as 3-CA degrader. Using replicated reactors, this study has demonstrated the impact of a sustained stress on the activated sludge community and processes carried out by its members, followed by process recovery. By a combination of techniques, we showed that microbial communities can develop degradative capacity following a sustained xenobiotic input, and that targeted culture-independent approaches can suggest plausible mechanisms for 3-CA degradation and identify the taxa potentially contributing to it.

microbiology↗
bioRxiv2020

Analysis procedures for assessing recovery of high quality, complete, closed genomes from Nanopore long read metagenome sequencing

New long read sequencing technologies offer huge potential for effective recovery of complete, closed genomes from complex microbial communities. Using long read (MinION) obtained from an ensemble of activated sludge enrichment bioreactors, we 1) describe new methods for validating long read assembled genomes using their counterpart short read metagenome assembled genomes; 2) assess the influence of different correction procedures on genome quality and predicted gene quality and 3) contribute 21 new closed or complete genomes of community members, including several species known to play key functional roles in wastewater bioprocesses: specifically microbes known to exhibit the polyphosphate- and glycogen-accumulating organism phenotypes (namely Accumulibacter and Dechloromonas, and Micropruina and Defluviicoccus, respectively), and filamentous bacteria (Thiothrix) associated with the formation and stability of activated sludge flocs. Our findings further establish the feasibility of long read metagenome-assembled genome recovery, and demonstrate the utility of parallel sampling of moderately complex enrichments communities for recovery of genomes of key functional species relevant for the study of complex wastewater treatment bioprocesses.

bioinformatics↗
bioRxiv2020

Species level enrichment of AnAOB and associated growth morphology under the effect of key metabolites

Nineteen anaerobic ammonium oxidizing bacteria (AnAOB) species have been identified, yet the environmental factors that select for each species within a specialized ecological niche have not been described. We enriched AnAOB from a single inoculum under standard enrichment conditions (reactor R1) with stepwise increase in nitrite and ammonia concentration, nitric oxide (NO) supplementation (reactor R2), or with complex organic carbon using wastewater collected from mainstream wastewater treatment facility (reactor R3). AnAOB were enriched up to 80%, 90% and 50% relative abundance in R1, R2 and R3 respectively. Candidatus Brocadia caroliniensis predominated in all reactors, but a shift towards Ca. Brocadia sinica was consistently observed with increasing ammonium and nitrite concentrations beyond 270 mg NH4-N L-1 and 340 mg NO2-N L-1, respectively. In the presence of NO, growth of heterotrophs were inhibited, and Ca. Jettenia could coexist with Ca. B. caroliniensis before diminishing when nitrite increased to 160 mg NO2-N L-1. In contrast, supplementation of organic carbon led to the emergence of heterotrophic communities that coevolved with Ca. B. caroliniensis. Ca. B. caroliniensis and Ca. Jettenia preferentially form biofilms on reactor surfaces, whereas Ca. Brocadia sinica forms granules in suspension. Our results thus indicate that multiple AnAOB species co-exist and occupy sub-niches in anaerobic ammonium oxidation reactors, that the dominant population can be reversibly shifted by, for example, changing the nitrogen load (i.e. high nitrite concentration favors Ca. Brocadia caroliniensis), and that speciation has implications for wastewater process design, with the optimum cell immobilization strategy (i.e. carriers vs granules) dependent on which species dominates. IMPORTANCEThis study demonstrates how to reversibly and predictably shift dominant anammox population using operating parameters (e.g. high nitrite concentration favours Ca. Brocadia sinica), and that species selection has implications for wastewater process design, illustrated here in terms of dependence of optimum cell immobilization strategy (i.e. carriers vs granules) on which species dominates. The research informs the characterization of AnAOBs at species level as well process design and control strategies targeting Anammox species population dynamics in full scale waste water treatment systems.

ecology↗
bioRxiv2018

Apparent oxygen half saturation constant for nitrifiers: genus specific, inherent physiological property, or artefact of colony morphology?

We report that a single Nitrospira sublineage I OTU performs nitrite oxidation in several full-scale domestic wastewater treatment plants (WWTPs) in the tropics (29-31 {degrees}C). Contrary to the prevailing theory for the relationship between nitrite oxidizing bacteria (NOB) and ammonia oxidizing bacteria (AOB), members of the Nitrospira sublineage I OTU had an apparent half saturation coefficient, Ks(app) lower than that of the full-scale domestic activated sludge cohabitant AOB (0.09 {+/-} 0.02 g O2 m-3 versus 0.3 {+/-} 0.03 g O2 m-3). Paradoxically, NOB may thus thrive under conditions of low oxygen supply. Low dissolved oxygen (DO) conditions could enrich for and high aeration inhibit the NOB in a long-term lab-scale reactor. The relative abundance of Nitrospira gradually decreased with increasing DO until it was washed out. Nitritation was sustained even after the DO was lowered subsequently. Based on 3D-fluorescence in situ hybridization (FISH) image analysis, the morphologies of AOB and NOB microcolonies responded to DO levels in accordance with their apparent oxygen half saturation constant Ks(app). When exposed to the same oxygenation level, NOB formed densely packed spherical clusters with a low surface area-to-volume ratio compared to the Nitrosomonas-like AOB clusters, which maintained a porous and non-spherical morphology. Microcolony morphology is thus a way for AOB and NOB to regulate oxygen exposure and sustain the mutualistic interaction. However, short-term high DO exposure can select for AOB and against NOB in full-scale domestic WWTPs and such population dynamics depend on which specific AOB and NOB species predominate under given environmental conditions.

systems biology↗
bioRxiv2017

MEGAN-LR: New algorithms allow accurate binning and easy interactive exploration of metagenomic long reads and contigs

BackgroundThere are numerous computational tools for taxonomic or functional analysis of microbiome samples, optimized to run on hundreds of millions of short, high quality sequencing reads. Programs such as MEGAN allow the user to interactively navigate these large datasets. Long read sequencing technologies continue to improve and produce increasing numbers of longer reads (of varying lengths in the range of 10k-1M bps, say), but of low quality. There is an increasing interest in using long reads in microbiome sequencing and there is a need to adapt short read tools to long read datasets.\n\nMethodsWe describe a new LCA-based algorithm for taxonomic binning, and an interval-tree based algorithm for functional binning, that are explicitly designed for long reads and assembled contigs. We provide a new interactive tool for investigating the alignment of long reads against reference sequences. For taxonomic and functional binning, we propose to use LAST to compare long reads against the NCBI-nr protein reference database so as to obtain frame-shift aware alignments, and then to process the results using our new methods.\n\nResultsAll presented methods are implemented in the open source edition of MEGAN and we refer to this new extension as MEGAN-LR (MEGAN long read). We evaluate the LAST+MEGAN-LR approach in a simulation study, and on a number of mock community datasets consisting of Nanopore reads, PacBio reads and assembled PacBio reads. We also illustrate the practical application on a Nanopore dataset that we sequenced from an anammox bio-rector community.

bioinformatics↗
bioRxiv2017

Enterococcus faecalis Promotes Innate Immune Suppression And Polymicrobial Catheter-Associated Urinary Tract Infection

Enterococcus faecalis, a member of the human gastrointestinal microbiota, is an opportunistic pathogen associated with hospital-acquired wound, bloodstream, and urinary tract infections. E. faecalis can subvert or evade immune-mediated clearance, although the mechanisms are poorly understood. In this study, we examined E. faecalis-mediated subversion of macrophage activation. We observed that E. faecalis actively prevents NF-{kappa}B signaling in mouse RAW264.7 macrophages in the presence of Toll-like receptor agonists and during polymicrobial infection with Escherichia coli. E. faecalis and E. coli co-infection in a mouse model of catheter-associated urinary tract infection (CAUTI) resulted in a suppressed macrophage transcriptional response in the bladder compared to E. coli infection alone. Finally, we demonstrated that co-inoculation of E. faecalis with E. coli into catheterized bladders significantly augmented E. coli CAUTI. Taken together, these results support that E. faecalis suppression of NF-{kappa}B-driven responses in macrophages promotes polymicrobial CAUTI pathogenesis.\n\nAuthor SummarySynergistic polymicrobial infections can contribute to both disease severity and persistence. Enterococcus faecalis and Escherichia coli are frequently co-isolated from polymicrobial urinary tract infections. Immunomodulation by co-infecting microbes can result in a more permissive environment for pathogens to establish infection. Presently, we do not yet understand how these microbes overcome host immunity to establish polymicrobial infections. To address this, we investigated how the immunosuppressive function of E. faecalis can contribute to acute infection. We defined that E. faecalis is able to suppress macrophages in vitro, despite the presence of E. coli. We also demonstrated E. faecalis ability to augment E. coli titers in vivo to establish kidney infection. Our findings raise the prospect that E. faecalis can alter host immunity to increase susceptibility to other uropathogens.

microbiology↗
bioRxiv2017

Draft Genome Sequence Of A Candidatus Brocadia Bacterium Enriched From Tropical-Climate Activated Sludge

We present the draft genome of an anaerobic ammonium-oxidizing (anammox) bacterium, cluster III Candidatus Brocadia, which was enriched in an anammox reactor. A 3.2 Mb genome sequence comprising 168 contigs was assembled, in which 2,765 gene-coding regions, 47 tRNAs, and 5S, 16S and 23S ribosomal RNAs were annotated. No evidence for the presence of a nitric oxide-forming nitrite reductase was found.

microbiology↗
bioRxiv2017

Extracellular Electron Transfer Powers Enterococcus faecalis Biofilm Metabolism

Enterococci are important human commensals and significant opportunistic pathogens associated with endocarditis, urinary tract infections, wound and surgical site infections, and medical device associated infections. These infections often become chronic upon the formation of biofilm. The biofilm matrix establishes properties that distinguish this state from free-living bacterial cells and increase tolerance to antimicrobial interventions. The metabolic versatility of the Enterococci is reflected in the diversity and complexity of environments and communities in which they thrive. Understanding metabolic factors governing colonization and persistence in different host niches can reveal factors influencing the transition from commensal to opportunistic pathogen. Here, we report a new form of iron-dependent metabolism for Enterococcus faecalis where, in the absence of heme, respiration components can be utilised for extracellular electron transfer (EET). Iron augments E. faecalis biofilm growth and generates alterations in biofilm matrix, cell spatial distribution, and biofilm matrix properties. We identify the genes involved in iron-augmented biofilm growth and show that it occurs by promoting EET to iron within biofilm.\n\nSignificanceBacterial metabolic versatility is often key in dictating the outcome of host-pathogen interactions, yet determinants of metabolic shifts are difficult to resolve. The bacterial biofilm matrix provides the structural and functional support that distinguishes this state from free-living bacterial cells. Here, we show that the biofilm matrix provides access to resources necessary for metabolism and growth which are otherwise inaccessible in the planktonic state. Our data shows that in the absence of heme, components of Enterococcus faecalis respiration (l-lactate dehydrogenase and acetaldehyde dehydrogenase) may function as initiators of EET through the cytoplasmic membrane quinone pool and utilize matrix-associated iron to carry out EET. The presence of iron resources within the biofilm matrix leads to enhanced biofilm growth.

microbiology↗
bioRxiv2016

The detection of covariation of mRNA levels of large sets of genes across multiple human populations

In this study, we analyse RNA-Seq data from panels of human lymphoblastoid cell lines (LCLs) to identify covariation in the mRNA levels of large numbers of genes. Such large scale covariation may have biological origin or be due to technical variation in analysis (generally referred to as batch effects). We show that batch effects cannot explain this covariation by demonstrating reproducibility across different human populations and across different methods of analysis. This view is also supported by enrichment of single and combinations of transcription factors (TFs) binding to cognate promoter regions, enrichment of genes shown to be sensitive to the knockdown of individual TFs, enrichment of functional pathways, and finally enrichment of protein-protein interactions in proteins encoded by groups of covarying genes. The properties of the groups of covarying genes are therefore most readily explained by the influence of cumulative variations in the effectors of gene expression that act in trans on cognate genes. We suggest that covariation has functional outcomes by showing that covariation of 83 genes involved in the spliceosome pathway accounts for 8-16% of the variation in the alternative splicing patterns of genes expressed in human LCLs.

genetics↗