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bioRxiv2017

The CURE for Culturing Fastidious Microbes

Course-based Undergraduate Research Experiences (CUREs) expand the scientific educational benefits of research to large groups of students in a course setting. As part of an ongoing effort to integrate CUREs into first-year biology labs, we developed a microbiology CURE (mCURE) that uses a modified dilution-to-extinction high throughput culturing protocol for isolating abundant yet fastidious aquatic bacterioplankton during one semester. Students learn common molecular biology techniques like nucleic acid extraction, PCR, and molecular characterization; read and evaluate scientific literature; and receive training in scientific communication through written and oral exercises that incorporate social media elements. In the first three semesters, the mCUREs achieved similar cultivability success as implementation of the protocol in a standard laboratory setting. Our modular framework facilitates customization of the curriculum for use in multiple settings and we provide classroom exercises, assignments, assessment tools, and examples of student output to assist with implementation.

scientific communication and education↗

bioRxiv2017

A plasmid-based Escherichia coli gene expression system with cell-to-cell variation below the extrinsic noise limit

Experiments in synthetic biology and microbiology can benefit from protein expression systems with low cell-to-cell variability (noise) and expression levels precisely tunable across a useful dynamic range. Despite advances in understanding the molecular biology of microbial gene regulation, many experiments employ protein-expression systems exhibiting high noise and nearly all-or-none responses to induction. I present an expression system that incorporates elements known to reduce gene expression noise: negative autoregulation and bicistronic transcription. I show by stochastic simulation that while negative autoregulation can produce a more gradual response to induction, bicistronic expression of a repressor and gene of interest can be necessary to reduce noise below the extrinsic limit. I synthesized a plasmid-based system incorporating these principles and studied its properties in Escherichia coli cells, using flow cytometry and fluorescence microscopy to characterize induction dose-response, induction/repression kinetics and gene expression noise. By varying ribosome binding site strengths, expression levels from 55-- 10,740 molecules/cell were achieved with noise below the extrinsic limit. Individual strains are inducible across a dynamic range greater than 20-fold. Experimental comparison of different regulatory networks confirmed that bicistronic autoregulation reduces noise, and revealed unexpectedly high noise for a conventional expression system with a constitutively expressed transcriptional repressor. I suggest a hybrid, low-noise expression system to increase the dynamic range.

synthetic biology↗

bioRxiv2017

Low cost and open source multi-fluorescence imaging system for teaching and research in biology and bioengineering

The advent of easy-to-use open source microcontrollers, off-the-shelf electronics and customizable manufacturing technologies has facilitated the development of inexpensive scientific devices and laboratory equipment. In this study, we describe an imaging system that integrates low-cost and open-source hardware, software and genetic resources. The multi-fluorescence imaging system consists of readily available 470 nm LEDs, a Raspberry Pi camera and a set of filters made with low cost acrylics. This device allows imaging in scales ranging from single colonies to entire plates. We developed a set of genetic components (e.g. promoters, coding sequences, terminators) and vectors following the standard framework of Golden Gate, which allowed the fabrication of genetic constructs in a combinatorial, low cost and robust manner. In order to provide simultaneous imaging of multiple wavelength signals, we screened a series of long stokes shift fluorescent proteins that could be combined with cyan/green fluorescent proteins. We found CyOFP1, mBeRFP and sfGFP to be the most compatible set for 3-channel fluorescent imaging. We developed open source Python code to operate the hardware to run time-lapse experiments with automated control of illumination and camera and a Python module to analyze data and extract meaningful biological information. To demonstrate the potential application of this integral system, we tested its performance on a diverse range of imaging assays often used in disciplines such as microbial ecology, microbiology and synthetic biology. We also assessed its potential for STEM teaching in a high school environment, using it to teach biology, hardware design, optics, and programming. Together, these results demonstrate the successful integration of open source hardware, software, genetic resources and customizable manufacturing to obtain a powerful, low cost and robust system for STEM education, scientific research and bioengineering. All the resources developed here are available under open source licenses.

synthetic biology↗

bioRxiv2017

Bdellovibrio and like organisms bacterial predators are not equally distributed in peri-alpine lakes

Microbes drive a variety of ecosystem processes and services but still many of them remain largely unexplored because of our lack of knowledge on both diversity and functionality of some potentially key microbiological compartments. This is typically the case with and within the group of bacterial predators collectively known as Bdellovibrio and like organisms (BALOs). Here we report for the first time the abundance, distribution and diversity of the three main families of these natural and obligatory predators of gram negative bacteria in three peri-alpine lakes (e.g. lakes Annecy, Bourget and Geneva) at different depths (surface vs. 45 or 50 m) and along a few months (from August 2015 to January 2016). We show that, using PCR-DGGE and cloning-sequencing approaches, the diversity appeared relatively low and very specific to fresh waters or even of the lakes themselves. While the Peredibacteraceae family was represented mainly by a single species (i.e. Peredibacter starii), it could constitute up to 7% of the total bacterial cell abundances. Comparati vel y, the abundances of the two other families (referred to as Bdellovibrionaceae and Bacteriovaracaceae) were significantly lower. More interestingly, the distribution in the water column was very different between the three groups suggesting various life strategies/niches for each of them: Peredibactereacea dominated near surface while the Bdellovibrionaceae and the Bacteriovaracaceae were more abundant at depth. All in all, our results suggest that these bacterial predators are likely to play a significant role in mortality, carbon fluxes and prokaryotic community structure in lakes.

ecology↗

bioRxiv2017

Fitting functional responses: Direct parameter estimation by simulating differential equations

O_LIThe feeding functional response is one of the most widespread mathematical frameworks in Ecology, Marine Biology, Freshwater Biology, Microbiology and related scientific fields describing the resource-dependent uptake of a consumer. Since the exact knowledge of its parameters is crucial in order to predict, for example, the efficiency of biocontrol agents, population dynamics, food web structure and subsequently biodiversity, a trustful parameter estimation is of utmost importance for scientists using this framework. Classical approaches for estimating functional response parameters lack flexibility and can often only serve as approximation for a correct parameter estimation. Moreover, they do not allow to incorporate side effects such as resource growth or background mortality. Both call for a new method to be established solving these problems.\nC_LIO_LIHere, we combined ordinary differential equation models (ODE models), that were numerically solved using computer simulations, with an iterative maximum likelihood fitting approach. We compared our method to classical approaches of fitting functional responses, using data both with and without additional resource growth and mortality.\nC_LIO_LIWe found that for classical functional response models, like the often used type II and type III functional response, the established fitting methods are reliable. However, using more complex and flexible functional responses, our new established method outperforms the traditional methods. Additionally, only our method allows to analyze experiments correctly when resources experience growth or background mortality.\nC_LIO_LIOur method will enable researchers from different scientific fields that are measuring functional responses to estimate parameters correctly. These estimates will enable community ecologists to parameterize their models more precisely, allowing for a deeper understanding of complex ecological systems, and will increase the quality of ecological prediction models.\nC_LI

ecology↗

bioRxiv2019

Two distinct bacterial biofilm components trigger metamorphosis in the colonial hydrozoan Hydractinia echinata

In the marine environment bacterial-induced metamorphosis of larvae is a widespread cross-kingdom communication phenomenon and critical for the persistence of many marine invertebrates. However, the identities of most inducing bacterial signals and the underlying cellular mechanisms remain enigmatic. Larvae of Hydractinia echinata provide an excellent model for investigating bacteria-stimulated settlement as they transform upon detection of the signal into the colonial adult stage within 24 h. Although H. echinata served as cell biological model system for decades, the influence of bacterial signals on the morphogenic transition remained largely unexplored. Using a bioassay-guided analysis, we first identified that specific bacterial (lyso)phospholipids, naturally present in bacterial biofilms, elicit metamorphosis in Hydractinia larvae in a dose-response matter. In particular, lysophospholipids as single compounds or in combinations at 50 {micro}M concentrations induced metamorphosis in up to 50% of all larvae phospholipid within 48 h. By using fluorescence-labeled bacterial phospholipids, we demonstrated their incorporation into the larval membranes, where interactions with internal signaling cascades could occur. In addition, two structurally distinct exopolysaccharides, the newly identified Rha-Man polysaccharide from Pseudoalteromonas sp. P1-9 and curdlan from Alcaligenes faecalis caused up to 75% of all larvae to transform within 24 h. We also found that combinations of (lyso)phospholipids and curdlan induced the transformation in almost all larvae within 24 h, thereby exceeding the morphogenic activity observed for single compounds and axenic bacterial biofilms. Our results demonstrate that multiple and structurally distinct bacterial-derived metabolites converge to induce high transformation rates of Hydractinia larvae, which might ensure optimal habitat selection despite the general widespread occurrence of both compound classes. Significance StatementBacterial biofilms profoundly influence the recruitment and settlement of marine invertebrates, critical steps for diverse marine processes such as coral reef formation, marine fisheries and the fouling of submerged surfaces. Yet, the complex composition of biofilms often makes it challenging to characterize the individual signals and regulatory mechanisms. Developing tractable model systems to characterize these co-evolved interactions is the key to understand fundamental processes in evolutionary biology. Here, we characterized for the first time two types of bacterial signaling molecules that induce the morphogenic transition and analyzed their abundance and combinatorial activity. This study highlights the crucial role of the converging activity of multiple bacterial signals in development-related cross-kingdom signaling. AreasMajor: Chemical Biology, Microbiology, Developmental Biology

ecology↗

bioRxiv2020

Simultaneous Discovery of Positive and Negative Interactions Among Root Microbiome Bacteria Using Microwell Recovery Arrays

Understanding the consequences of microbe-microbe interactions is critical in efforts to predict the function of microbiomes and to manipulate or construct communities to achieve desired outcomes. The investigation of these interactions poses a significant challenge - in part due to the lack of suitable experimental tools. We present the Microwell Recovery Array, a high throughput approach designed to rapidly screen interactions across a microbiome and uncover higher-order combinations of strains that either inhibit or promote the function of a GFP-producing focal species. One experiment generates 104 unique microbial communities that contain a focal species combined with a unique combination of previously uncharacterized cells from plant rhizosphere. Cells are then sequentially extracted from individual co-culture wells that display highest or lowest levels of focal species function using a novel high-resolution photopolymer extraction system. Microbes present are subsequently identified and the putative interactions are validated. Using this approach, we screen the Populus trichocarpa rhizosphere for bacterial strains affecting the survival and growth of Pantoea sp. YR343, a plant growth promoting strain isolated from the P. trichocarpa rhizosphere. We were able to simultaneously isolate and validate multiple Stenotrophomonas strains that antagonize strain YR343 growth and a set of Enterobacter strains that promote strain YR343 growth. The latter demonstrates the unique ability of the platform to uncover multi-membered consortia that generate emergent phenotypes. This knowledge will inform the development of beneficial consortia that promote the production of Populus biofuel feedstock, while the platform is adaptable to screening higher-order interactions in any microbiome of interest. Significance StatementAchieving a fundamental understanding of microbe-microbe interactions that occur within microbial communities is a grand challenge in microbiology due to the limited experimental tools available. In this report, we describe a new tool that enables one to screen microbial interactions across thousands of compositionally unique communities to discover collections of bacteria that antagonize or promote the survival and growth of bacteria with important functions. This approach has the unique ability to uncover higher-order combinations of bacteria that generate emergent phenotypes, information useful for development of biofertilizer, biocontrol, or probiotic consortia, as well as in the design of communities for biosynthetic compound production.

bioengineering↗

bioRxiv2020

Glacier ice archives fifteen-thousand-year-old viruses

While glacier ice cores provide climate information over tens to hundreds of thousands of years, study of microbes is challenged by ultra-low-biomass conditions, and virtually nothing is known about co-occurring viruses. Here we establish ultra-clean microbial and viral sampling procedures and apply them to two ice cores from the Guliya ice cap (northwestern Tibetan Plateau, China) to study these archived communities. This method reduced intentionally contaminating bacterial, viral, and free DNA to background levels in artificial-ice-core control experiments, and was then applied to two authentic ice cores to profile their microbes and viruses. The microbes differed significantly across the two ice cores, presumably representing the very different climate conditions at the time of deposition that is similar to findings in other cores. Separately, viral particle enrichment and ultra-low-input quantitative viral metagenomic sequencing from [~]520 and [~]15,000 years old ice revealed 33 viral populations (i.e., species-level designations) that represented four known genera and likely 28 novel viral genera (assessed by gene-sharing networks). In silico host predictions linked 18 of the 33 viral populations to co-occurring abundant bacteria, including Methylobacterium, Sphingomonas, and Janthinobacterium, indicating that viruses infected several abundant microbial groups. Depth-specific viral communities were observed, presumably reflecting differences in the environmental conditions among the ice samples at the time of deposition. Together, these experiments establish a clean procedure for studying microbial and viral communities in low-biomass glacier ice and provide baseline information for glacier viruses, some of which appear to be associated with the dominant microbes in these ecosystems. ImportanceThis study establishes ultra-clean microbial and viral sampling procedures for glacier ice, which complements prior in silico decontamination methods and expands, for the first time, the clean procedures to viruses. Application of these methods to glacier ice confirmed prior common microbiological findings for a new ice core climate record, and provides a first window into viral genomes and their ecology from glacier ice across two time horizons, and emphasizes their likely impact on abundant microbial groups. Together these efforts provide clean sampling approaches and foundational datasets that should enable simultaneous access to an archived virosphere in glacier ice.

ecology↗

bioRxiv2020

Metagenomics workflow for hybrid assembly, differential coverage binning, transcriptomics and pathway analysis (MUFFIN)

Metagenomics has redefined many areas of microbiology. However, metagenome-assembled genomes (MAGs) are often fragmented, primarily when sequencing was performed with short reads. Recent long-read sequencing technologies promise to improve genome reconstruction. However, the integration of two different sequencing modalities makes downstream analyses complex. We, therefore, developed MUFFIN, a complete metagenomic workflow that uses short and long reads to produce high-quality bins and their annotations. The workflow is written by using Nextflow, a workflow orchestration software, to achieve high reproducibility and fast and straightforward use. This workflow also produces the taxonomic classification and KEGG pathways of the bins and can be further used by providing RNA-Seq data (optionally) for quantification and annotation. We tested the workflow using twenty biogas reactor samples and assessed the capacity of MUFFIN to process and output relevant files needed to analyze the microbial community and their function. MUFFIN produces functional pathway predictions and if provided de novo transcript annotations across the metagenomic sample and for each bin. Author SummaryRVD did the development and design of MUFFIN and wrote the first draft; BM and EBR did the critical reading and correction of the manuscript; MH did the critical reading of the manuscript and the general adjustments for the metagenomic workflow; AV did the critical reading of the manuscript and adjustments for the taxonomic classifications. CB supervised the project, did the workflow design, helped with the implementation, and revised the manuscript.

bioinformatics↗

bioRxiv2020

mAML: an automated machine learning pipeline with a microbiome repository for human disease classification

Due to the concerted efforts to utilize the microbial features to improve disease prediction capabilities, automated machine learning (AutoML) systems designed to get rid of the tediousness in manually performing ML tasks are in great demand. Here we developed mAML, an ML model-building pipeline, which can automatically and rapidly generate optimized and interpretable models for personalized microbial classification tasks in a reproducible way. The pipeline is deployed on a web-based platform and the server is user-friendly, flexible, and has been designed to be scalable according to the specific requirements. This pipeline exhibits high performance for 13 benchmark datasets including both binary and multi-class classification tasks. In addition, to facilitate the application of mAML and expand the human disease-related microbiome learning repository, we developed GMrepo ML repository (GMrepo Microbiome Learning repository) from the GMrepo database. The repository involves 120 microbial classification tasks for 85 human-disease phenotypes referring to 12,429 metagenomic samples and 38,643 amplicon samples. The mAML pipeline and the GMrepo ML repository are expected to be important resources for researches in microbiology and algorithm developments. Database URLhttp://39.100.246.211:8050/Home

bioinformatics↗

bioRxiv2020

SIV and Mycobacterium tuberculosis synergy within the granuloma accelerates the reactivation pattern of latent tuberculosis

Human immunodeficiency virus infection is the most common risk factor for severe forms of tuberculosis (TB), regardless of CD4 T cell count. Using a well-characterized cynomolgus macaque model of human TB, we compared radiographic, immunologic and microbiologic characteristics of early (subclinical) reactivation of latent M. tuberculosis (Mtb) infection among animals subsequently infected with simian immunodeficiency virus (SIV) or who underwent anti-CD4 depletion by a depletion antibody. CD4 depleted animals had significantly fewer CD4 T cells within granulomas compared to Mtb/SIV co-infected and Mtb-only control animals. After 2 months of treatment, subclinical reactivation occurred at similar rates among CD4 depleted (5 of 7 animals) and SIV infected animals (4 of 8 animals). However, SIV-induced reactivation was associated with more dissemination of lung granulomas that were permissive to Mtb growth resulting in greater bacterial burden within granulomas compared to CD4 depleted reactivators. Granulomas from Mtb/SIV animals displayed a more robust T cell activation profile (IFN-, IFN-{gamma}, TNF, IL-17, IL-2, IL-10, IL-4 and granzyme B) compared to Mtb/CD4 animals and controls though these effectors did not protect against reactivation or dissemination, but instead may be related to increased viral and/or Mtb antigens. SIV replication within the granuloma was associated with reactivation, greater overall Mtb growth and Mtb killing resulting in greater overall Mtb burden. These data support that SIV disrupts protective immune responses against latent Mtb infection beyond the loss of CD4 T cells, and that synergy between SIV and Mtb occurs within granulomas. Author SummaryMost humans are able to control infection with Mycobacterium tuberculosis (Mtb), the bacteria that causes tuberculosis (TB). Controlled, asymptomatic infection (latent infection) can develop into symptomatic, severe TB (reactivation TB) when the immune system is impaired, and HIV is the most common risk factor. Chronic HIV infection is associated with low CD4 T cells but there are likely other factors involved. Using macaques with latent Mtb infection, we could induce reactivation from either CD4 T cell depletion or SIV infection. We found that SIV induced reactivation was more dramatic with more bacterial dissemination and bacterial growth compared to those with CD4 depletion. While SIV-infected animals had more activated immune responses in the lung granulomas (a collection of immune cells that functions to combat Mtb), they could not prevent bacterial spread of Mtb resulting in more TB pathology, higher bacterial burden and disease throughout the body. These data suggest that the HIV-induced reactivation TB is not solely from the loss of CD4 T cells. Furthermore, our data suggest that SIV and Mtb have a synergistic relationship within granulomas that impairs the ability to kill Mtb and that this relationship exacerbates TB disease.

immunology↗

bioRxiv2020

Optimization of data-independent acquisition using predicted libraries for deep and accurate proteome profiling

In silico spectral library prediction of all possible peptides from whole organisms has a great potential for improving proteome profiling by data-independent acquisition (DIA) and extending its scope of application. In combination with other recent improvements in the field of mass spectrometry (MS)-based proteomics, including sample preparation, peptide separation and data analysis, we aimed to uncover the full potential of such an advanced DIA strategy by optimization of the data acquisition. The results demonstrate that the combination of high-quality in silico libraries, reproducible and high-resolution peptide separation using micro-pillar array columns as well as neural network supported data analysis enables the use of long MS scan cycles without impairing the quantification performance. The study demonstrates that mean coefficient of variations of 4 % were obtained even at only 1.5 data points per peak (full width at half maximum) across different gradient lengths, which in turn improved proteome coverage up to more than 8000 proteins from HeLa cells using empirically-corrected libraries and more than 7000 proteins using a whole human in silico predicted library. These data were obtained using a Q Exactive orbitrap mass spectrometer with moderate scanning speed (12 Hz) and perform very well in comparison to recent studies using more advanced MS instruments, which underline the high potential of this optimization strategy for various applications in clinical proteomics, microbiology and molecular biology.

systems biology↗

bioRxiv2020

Repetitive Transcranial Magnetic Stimulation Activates Glial Cells and Inhibits Neurogenesis after Pneumococcal Meningitis

Pneumococcal meningitis (PM) causes damage to the hippocampus, a brain structure critically involved in learning and memory. Hippocampal injury - which compromises neurofunctional outcome - occurs as apoptosis of progenitor cells and immature neurons of the hippocampal dentate granule cell layer thereby impairing the regenerative capacity of the hippocampal stem cell niche. Repetitive transcranial magnetic stimulation (rTMS) harbours the potential to modulate the proliferative activity of this neuronal stem cell niche. In this study, specific rTMS protocols - namely continuous and intermittent theta burst stimulation (cTBS and iTBS) - were applied on infant rats microbiologically cured from PM by five days of antibiotic treatment. Following two days of exposure to TBS, differential gene expression was analysed by whole transcriptome analysis using RNAseq. cTBS provoked a prominent effect in inducing differential gene expression in the cortex and the hippocampus, whereas iTBS only affect gene expression in the cortex. TBS induced polarisation of microglia and astrocytes towards an inflammatory phenotype, while reducing neurogenesis, neuroplasticity and regeneration. cTBS was further found to induce the release of pro-inflammatory cytokines in vitro. We conclude that cTBS intensified neuroinflammation after PM, which translated into increased release of pro-inflammatory mediators thereby inhibiting neuroregeneration.

neuroscience↗

bioRxiv2020

NMR microsystem for label-free characterization of 3D nanoliter microtissues

Performing chemical analysis at the nanoliter (nL) scale is of paramount importance for medicine, drug development, toxicology, and research. Despite the numerous methodologies available, a tool for obtaining chemical information non-invasively is still missing at this scale. Observer effects, sample destruction and complex preparatory procedures remain a necessary compromise1. Among non-invasive spectroscopic techniques, one able to provide holistic and highly resolved chemical information in-vivo is nuclear magnetic resonance (NMR)2,3. For its renowned informative power and ability to foster discoveries and life-saving applications4,5, efficient NMR at microscopic scales is highly sought after6-10, but so far technical limitations could not match the stringent necessities of microbiology, such as biocompatible handling, ease of use, and high throughput. Here we introduce a novel microsystem, which combines CMOS technology with 3D microfabrication, enabling nL NMR as a platform tool for non-invasive spectroscopy of organoids, 3D cell cultures, and early stage embryos. In this study we show its application to microlivers models simulating non-alcoholic fatty liver disease (NAFLD), demonstrating detection of lipid metabolism dynamics in a time frame of 14 days based on 117 measurements of single 3D human liver microtissues.

bioengineering↗

bioRxiv2020

The archives are half-empty: a field-wide assessment of the availability of microbial community sequencing data

The sequencing revolution has resulted in the explosive growth of public genetic repositories. These repositories now hold invaluable collections of 16S rRNA gene amplicon sequences, but the extent to which the currently archived data is findable, accessible, and reusable has not been evaluated. We conducted a field-wide assessment of the availability and state of publicly archived 16S rRNA gene amplicon sequencing data. Using custom-built pattern-based text extraction algorithms, we searched 26,927 publications in 17 microbiology or microbial ecology journals, and identified 2,015 studies which performed 16S rRNA gene amplicon sequencing. We found, for example, that 7.2% of these had not been made public at the time of analysis, a trend which increased over time. Of the 635 studies targeting the V3-V4 region of the 16S rRNA gene, 40.3% contained data which was not available or not reusable, and for 25.5% of the studies, faults in data formatting or data labelling were likely to create obstacles in data reuse. Taken together, only 34% of these datasets had potentially reusable data. Our study reveals significant gaps in the availability of currently deposited community sequencing data, identifies major contributors to data loss, and offers suggestions for improving data archiving practices in the future.

ecology↗

bioRxiv2020

Advanced Research Infrastructure for Experimentation in genomicS (ARIES): a lustrum of Galaxy experience

Background: With the introduction of Next Generation Sequencing (NGS) and Whole-Genome Sequencing (WGS) in microbiology and molecular epidemiology, the development of an information system for the collection of genomic and epidemiological data and subsequent transparent and reproducible data analysis became indispensable. Further requirements for the system included accessibility and ease of use by bioinformatics as well as command line profane scientists. Findings: The ARIES (Advanced Research Infrastructure for Experimentation in genomicS, https://aries.iss.it) platform has been implemented in 2015 as an instance of the Galaxy framework specific for use of WGS in molecular epidemiology. Here, the experience with ARIES is reported. Conclusions: During its five years existence, ARIES has grown into a well-established reality not only as a web service but as well as a workflow engine for the Integrated Rapid Infectious Disease Analysis (IRIDA) platform. In fact, an environment has been created with the implementation of complex bioinformatic tools in an easy-to-use context allowing scientists to concentrate on what to do instead of how to do it.

bioinformatics↗

bioRxiv2020

Genomic diversity of Escherichia coli isolates from backyard chickens and guinea fowl in the Gambia

Chickens and guinea fowl are commonly reared in Gambian homes as affordable sources of protein. Using standard microbiological techniques, we obtained 68 caecal isolates of Escherichia coli from ten chickens and nine guinea fowl in rural Gambia. After Illumina whole-genome sequencing, 28 sequence types were detected in the isolates (four of them novel), of which ST155 was the most common (22/68, 32%). These strains span four of the eight main phylogroups of E. coli, with phylogroups B1 and A being most prevalent. Nearly a third of the isolates harboured at least one antimicrobial resistance gene, while most of the ST155 isolates (14/22, 64%) encoded resistance to [≥]3 classes of clinically relevant antibiotics, as well as putative virulence factors, suggesting pathogenic potential in humans. Furthermore, hierarchical clustering revealed that several Gambian poultry strains were closely related to isolates from humans. Although the ST155 lineage is common in poultry from Africa and South America, the Gambian ST155 isolates belong to a unique cgMLST cluster comprised of closely related (38-39 alleles differences) isolates from poultry and livestock from sub-Saharan Africa--suggesting that strains can be exchanged between poultry and livestock in this setting. Continued surveillance of E. coli and other potential pathogens in rural backyard poultry from sub-Saharan Africa is warranted. Author notesAll supporting data and protocols have been provided within the article or as supplementary data files. Eleven supplementary figures and eight supplementary files are available with the online version of this article. Data summaryThe genomic assemblies for the isolates reported here are available for download from EnteroBase (http://enterobase.warwick.ac.uk/species/index/ecoli) and the EnteroBase assembly barcodes are provided in File S2. Sequences have been deposited in the NCBI SRA, under the BioProject ID: PRJNA616250 and accession numbers SAMN14485281 to SAMN14485348 (File S2). Assemblies have been deposited in GenBank under the BioProject ID: PRJNA616250 and accession numbers CP053258 and CP053259. Impact statementDomestic birds play a crucial role in human society, in particular contributing to food security in low-income countries. Many households in Sub-Saharan Africa rear free-range chickens and guinea fowl, which are often left to scavenge for feed in and around the family compound, where they are frequently exposed to humans, other animals and the environment. Such proximity between backyard poultry and humans is likely to facilitate transmission of pathogens such as Escherichia coli or antimicrobial resistance between the two host species. Little is known about the population structure of E. coli in rural chickens and guinea fowl, although this information is needed to contextualise the potential risks of transmission of bacterial strains between humans and rural backyard poultry. Thus, we sought to investigate the genomic diversity of E. coli in backyard poultry from rural Gambia.

genomics↗

bioRxiv2020

Measuring both microbial load and diversity with a single amplicon sequencing library

The ratio of microbial population size relative to the amount of host tissue, or "microbial load", is a fundamental metric of colonization and infection, but it cannot be directly deduced from microbial amplicon data such as 16S rRNA gene counts. Because conventional methods to determine load, such as serial dilution plating or quantitative PCR, add substantial experimental burden, they are only rarely paired with amplicon sequencing. Alternatively, whole metagenome sequencing of DNA contributed by host and microbes both reveals microbial community composition and enables determination of microbial load, but host DNA typically greatly outweighs microbial DNA, severely limiting the cost-effectiveness and scalability of this approach. We introduce host-associated microbe PCR (hamPCR), a robust amplicon sequencing strategy to quantify microbial load and describe interkingdom microbial community composition in a single, cost-effective library. We demonstrate its accuracy and flexibility across multiple host and microbe systems, including nematodes and major crops. We further present a technique that can be used, prior to sequencing, to optimize the host representation in a batch of libraries without loss of information. Because of its simplicity, and the fact that it provides an experimental solution to the well-known statistical challenges provided by compositional data, hamPCR will become a transformative approach throughout culture-independent microbiology.

bioengineering↗