Loss of phenotypic inheritance associated with ydcI mutation leads to increased frequency of small, slow persisters in Escherichia coli.

Whenever a genetically homogenous population of bacterial cells is exposed to antibiotics, a tiny fraction of cells survives the treatment, the phenomenon known as bacterial persistence [G.L. Hobby et al., Exp. Biol. Med. 50, 281-285 (1942); J. Bigger, The Lancet 244, 497-500 (1944)]. Despite its biomedical relevance, the origin of the phenomenon is still unknown, and as a rare, phenotypically resistant subpopulation, persisters are notoriously hard to study and define. Using computerized tracking we show that persisters are small at birth and slowly replicating. We also determine that the high-persister mutant strain of Escherichia coli, HipQ, is associated with the phenotype of reduced phenotypic inheritance (RPI). We identify the gene responsible for RPI, ydcI, which encodes a transcription factor, and propose a mechanism whereby loss of phenotypic inheritance causes increased frequency of persisters. These results provide insight into the generation and maintenance of phenotypic variation and provide potential targets for the development of therapeutic strategies that tackle persistence in bacterial infections.

REM sleep's unique associations with corticosterone regulation, apoptotic pathways, and behavior in chronic stress in mice.

One of sleep's putative functions is mediation of adaptation to waking experiences. Chronic stress is a common waking experience; however, which specific aspect of sleep is most responsive, and how sleep changes relate to behavioral disturbances and molecular correlates remain unknown. We quantified sleep, physical, endocrine, and behavioral variables, as well as the brain and blood transcriptome in mice exposed to 9 weeks of unpredictable chronic mild stress (UCMS). Comparing 46 phenotypic variables revealed that rapid-eye-movement sleep (REMS), corticosterone regulation, and coat state were most responsive to UCMS. REMS theta oscillations were enhanced, whereas delta oscillations in non-REMS were unaffected. Transcripts affected by UCMS in the prefrontal cortex, hippocampus, hypothalamus, and blood were associated with inflammatory and immune responses. A machine-learning approach controlling for unspecific UCMS effects identified transcriptomic predictor sets for REMS parameters that were enriched in 193 pathways, including some involved in stem cells, immune response, and apoptosis and survival. Only three pathways were enriched in predictor sets for non-REMS. Transcriptomic predictor sets for variation in REMS continuity and theta activity shared many pathways with corticosterone regulation, in particular pathways implicated in apoptosis and survival, including mitochondrial apoptotic machinery. Predictor sets for REMS and anhedonia shared pathways involved in oxidative stress, cell proliferation, and apoptosis. These data identify REMS as a core and early element of the response to chronic stress, and identify apoptosis and survival pathways as a putative mechanism by which REMS may mediate the response to stressful waking experiences.

Symmetric metasurface with dual band polarization-independent high-Q resonances governed by symmetry-protected BIC.

In this Letter, we propose a symmetric metasurface composed of single-sized amorphous-silicon (a-Si) cuboids tetramer clusters that support two resonances with opposite symmetry, i.e., in-plane magnetic dipole (MD) resonance and in-plane toroidal dipole (TD) resonance governed by symmetry-protected bound states in the continuum (SP-BIC) in the near-infrared region. Since the cuboids tetramer of the metasurface retains C4v symmetry and mirror symmetry, both resonances are polarization independent. Multipolar decomposition of scattering power and electromagnetic distribution are performed to clarify the physical mechanism of dual quasi-BIC resonances. The effects of geometric parameters on both high-quality (Q) resonances are also studied. Additionally, the sensing performance of the designed metasurface is evaluated. The effects of the material's loss on both resonances are also studied. Our work provides a new route to designing dual mode polarization- independent resonators without multi-sized complex structures that may facilitate designing high-performance sensing applications.

A systematic evaluation of Mycobacterium tuberculosis Genome-Scale Metabolic Networks.

Metabolism underpins the pathogenic strategy of the causative agent of TB, Mycobacterium tuberculosis (Mtb), and therefore metabolic pathways have recently re-emerged as attractive drug targets. A powerful approach to study Mtb metabolism as a whole, rather than just individual enzymatic components, is to use a systems biology framework, such as a Genome-Scale Metabolic Network (GSMN) that allows the dynamic interactions of all the components of metabolism to be interrogated together. Several GSMNs networks have been constructed for Mtb and used to study the complex relationship between the Mtb genotype and its phenotype. However, the utility of this approach is hampered by the existence of multiple models, each with varying properties and performances. Here we systematically evaluate eight recently published metabolic models of Mtb-H37Rv to facilitate model choice. The best performing models, sMtb2018 and iEK1011, were refined and improved for use in future studies by the TB research community.

Direction-independent dual-band perfect absorption induced by fundamental magnetic polaritons.

In this paper, we designed a single sized Metal-Insulator Pair-Metal hybrid grating for dual-band perfect absorption from 8 µm to 14 µm utilizing both nondispersive insulators and dispersive phonic insulators. The hybrid grating was composed of Al/ZnTe-SiC pair/Al, which incorporated an ultrathin phononic SiC layer between the nondispersive ZnTe dielectric spacer and Al substrate. The physical mechanisms responsible for the dual-band perfect absorption were elucidated by the resonance of fundamental magnetic polaritons (MPs). Dual-band perfect absorption with incident angle insensitive feature was enabled. An equivalent LC circuit model predicting the dual-band resonant absorption peaks wavelengths was proposed and verified. Furthermore, the effects of grating period, strip width, nondispersive dielectric spacer thickness and polar phononic dielectric spacer thickness on the absorption were explored.

Comparative genomics of European avian pathogenic E. Coli (APEC).

BACKGROUND: Avian pathogenic Escherichia coli (APEC) causes colibacillosis, which results in significant economic losses to the poultry industry worldwide. However, the diversity between isolates remains poorly understood. Here, a total of 272 APEC isolates collected from the United Kingdom (UK), Italy and Germany were characterised using multiplex polymerase chain reactions (PCRs) targeting 22 equally weighted factors covering virulence genes, R-type and phylogroup. Following these analysis, 95 of the selected strains were further analysed using Whole Genome Sequencing (WGS). RESULTS: The most prevalent phylogroups were B2 (47%) and A1 (22%), although there were national differences with Germany presenting group B2 (35.3%), Italy presenting group A1 (53.3%) and UK presenting group B2 (56.1%) as the most prevalent. R-type R1 was the most frequent type (55%) among APEC, but multiple R-types were also frequent (26.8%). Following compilation of all the PCR data which covered a total of 15 virulence genes, it was possible to build a similarity tree using each PCR result unweighted to produce 9 distinct groups. The average number of virulence genes was 6-8 per isolate, but no positive association was found between phylogroup and number or type of virulence genes. A total of 95 isolates representing each of these 9 groupings were genome sequenced and analysed for in silico serotype, Multilocus Sequence Typing (MLST), and antimicrobial resistance (AMR). The UK isolates showed the greatest variability in terms of serotype and MLST compared with German and Italian isolates, whereas the lowest prevalence of AMR was found for German isolates. Similarity trees were compiled using sequencing data and notably single nucleotide polymorphism data generated ten distinct geno-groups. The frequency of geno-groups across Europe comprised 26.3% belonging to Group 8 representing serogroups O2, O4, O18 and MLST types ST95, ST140, ST141, ST428, ST1618 and others, 18.9% belonging to Group 1 (serogroups O78 and MLST types ST23, ST2230), 15.8% belonging to Group 10 (serogroups O8, O45, O91, O125ab and variable MLST types), 14.7% belonging to Group 7 (serogroups O4, O24, O35, O53, O161 and MLST type ST117) and 13.7% belonging to Group 9 (serogroups O1, O16, O181 and others and MLST types ST10, ST48 and others). The other groups (2, 3, 4, 5 and 6) each contained relatively few strains. However, for some of the genogroups (e.g. groups 6 and 7) partial overlap with SNPs grouping and PCR grouping (matching PCR groups 8 (13 isolates on 22) and 1 (14 isolates on 16) were observable). However, it was not possible to obtain a clear correlation between genogroups and unweighted PCR groupings. This may be due to the genome plasticity of E. coli that enables strains to carry the same virulence factors even if the overall genotype is substantially different. CONCLUSIONS: The conclusion to be drawn from the lack of correlations is that firstly, APEC are very diverse and secondly, it is not possible to rely on any one or more basic molecular or phenotypic tests to define APEC with clarity, reaffirming the need for whole genome analysis approaches which we describe here. This study highlights the presence of previously unreported serotypes and MLSTs for APEC in Europe. Moreover, it is a first step on a cautious reconsideration of the merits of classical identification criteria such as R typing, phylogrouping and serotyping.

Host-microbiome interactions in human type 2 diabetes following prebiotic fibre (galacto-oligosaccharide) intake.

Aberrant microbiota composition and function have been linked to several pathologies, including type 2 diabetes. In animal models, prebiotics induce favourable changes in the intestinal microbiota, intestinal permeability (IP) and endotoxaemia, which are linked to concurrent improvement in glucose tolerance. This is the first study to investigate the link between IP, glucose tolerance and intestinal bacteria in human type 2 diabetes. In all, twenty-nine men with well-controlled type 2 diabetes were randomised to a prebiotic (galacto-oligosaccharide mixture) or placebo (maltodextrin) supplement (5·5 g/d for 12 weeks). Intestinal microbial community structure, IP, endotoxaemia, inflammatory markers and glucose tolerance were assessed at baseline and post intervention. IP was estimated by the urinary recovery of oral 51Cr-EDTA and glucose tolerance by insulin-modified intravenous glucose tolerance test. Intestinal microbial community analysis was performed by high-throughput next-generation sequencing of 16S rRNA amplicons and quantitative PCR. Prebiotic fibre supplementation had no significant effects on clinical outcomes or bacterial abundances compared with placebo; however, changes in the bacterial family Veillonellaceae correlated inversely with changes in glucose response and IL-6 levels (r -0·90, P=0·042 for both) following prebiotic intake. The absence of significant changes to the microbial community structure at a prebiotic dosage/length of supplementation shown to be effective in healthy individuals is an important finding. We propose that concurrent metformin treatment and the high heterogeneity of human type 2 diabetes may have played a significant role. The current study does not provide evidence for the role of prebiotics in the treatment of type 2 diabetes.

Lipid metabolism and Type VII secretion systems dominate the genome scale virulence profile of Mycobacterium tuberculosis in human dendritic cells.

BACKGROUND: Mycobacterium tuberculosis continues to kill more people than any other bacterium. Although its archetypal host cell is the macrophage, it also enters, and survives within, dendritic cells (DCs). By modulating the behaviour of the DC, M. tuberculosis is able to manipulate the host's immune response and establish an infection. To identify the M. tuberculosis genes required for survival within DCs we infected primary human DCs with an M. tuberculosis transposon library and identified mutations with a reduced ability to survive. RESULTS: Parallel sequencing of the transposon inserts of the surviving mutants identified a large number of genes as being required for optimal intracellular fitness in DCs. Loci whose mutation attenuated intracellular survival included those involved in synthesising cell wall lipids, not only the well-established virulence factors, pDIM and cord factor, but also sulfolipids and PGL, which have not previously been identified as having a direct virulence role in cells. Other attenuated loci included the secretion systems ESX-1, ESX-2 and ESX-4, alongside many PPE genes, implicating a role for ESX-5. In contrast the canonical ESAT-6 family of ESX substrates did not have intra-DC fitness costs suggesting an alternative ESX-1 associated virulence mechanism. With the aid of a gene-nutrient interaction model, metabolic processes such as cholesterol side chain catabolism, nitrate reductase and cysteine-methionine metabolism were also identified as important for survival in DCs. CONCLUSION: We conclude that many of the virulence factors required for survival in DC are shared with macrophages, but that survival in DCs also requires several additional functions, such as cysteine-methionine metabolism, PGLs, sulfolipids, ESX systems and PPE genes.

Near-field radiative transfer between magneto-dielectric uniaxial anisotropic media.

We investigate the near-field radiative heat transfer between two semi-infinite magneto-dielectric uniaxial anisotropic media (MDUAM). SiC nanowires embedded in metamaterials are used to implement electric and magnetic anisotropy, which leads to the hyperbolic dispersion relation for both TE and TM waves. The results show that the TM and TE waves can support both hyperbolic modes and surface modes and that there exist additional modes contributing to the heat transfer for TE waves. Moreover, the MDUAM exhibit super-Planckian thermal emission at ultra-broad bandwidths. This work paves the way for applying the near-field radiative heat transfer in the area of thermal management and energy harvesting.

Mycobacterium leprae genomes from a British medieval leprosy hospital: towards understanding an ancient epidemic.

BACKGROUND: Leprosy has afflicted humankind throughout history leaving evidence in both early texts and the archaeological record. In Britain, leprosy was widespread throughout the Middle Ages until its gradual and unexplained decline between the 14th and 16th centuries. The nature of this ancient endemic leprosy and its relationship to modern strains is only partly understood. Modern leprosy strains are currently divided into 5 phylogenetic groups, types 0 to 4, each with strong geographical links. Until recently, European strains, both ancient and modern, were thought to be exclusively type 3 strains. However, evidence for type 2 strains, a group normally associated with Central Asia and the Middle East, has recently been found in archaeological samples in Scandinavia and from two skeletons from the medieval leprosy hospital (or leprosarium) of St Mary Magdalen, near Winchester, England. RESULTS: Here we report the genotypic analysis and whole genome sequencing of two further ancient M. leprae genomes extracted from the remains of two individuals, Sk14 and Sk27, that were excavated from 10th-12th century burials at the leprosarium of St Mary Magdalen. DNA was extracted from the surfaces of bones showing osteological signs of leprosy. Known M. leprae polymorphisms were PCR amplified and Sanger sequenced, while draft genomes were generated by enriching for M. leprae DNA, and Illumina sequencing. SNP-typing and phylogenetic analysis of the draft genomes placed both of these ancient strains in the conserved type 2 group, with very few novel SNPs compared to other ancient or modern strains. CONCLUSIONS: The genomes of the two newly sequenced M. leprae strains group firmly with other type 2F strains. Moreover, the M. leprae strain most closely related to one of the strains, Sk14, in the worldwide phylogeny is a contemporaneous ancient St Magdalen skeleton, vividly illustrating the epidemic and clonal nature of leprosy at this site. The prevalence of these type 2 strains indicates that type 2F strains, in contrast to later European and associated North American type 3 isolates, may have been the co-dominant or even the predominant genotype at this location during the 11th century.

Calculation method and analysis of residual stress in the strip bending roller straightening process.

Taking thin gauge strip as an example, the deformation process of metal strip in bending roll straightening was studied. Based on the theory of discrete, curvature integral and elastic-plastic mechanics, the strip travel trajectory of the bending roll straightening process is analyzed, and the numerical analytical calculation method of the continuous straightening process of the strip bending roll is established. The results are verified by establishing MARC finite element simulation and designing straightening experiment. The effects of yield strength, plastic rate and bending amount on residual stress after straightening were studied. In the straightening process, with the increase of the amount of bending roll, the residual strain converges to the region Γ, and with the increase of the yield strength, the region Γ decreases. With the increase of the yield strength, the amount of bending roll and the plastic rate, the wave height increases. The results of the calculation of residual stress, finite element simulation and experiment are close and the trend is consistent. The results show that the logic of the calculation method is reasonable, and the prediction error is within the scope of engineering application, which is helpful to the realization of process intelligence in the process of bending roller straightening.

Temporal genome-wide fitness analysis of Mycobacterium marinum during infection reveals the genetic requirement for virulence and survival in amoebae and microglial cells.

Tuberculosis remains the most pervasive infectious disease and the recent emergence of drug-resistant strains emphasizes the need for more efficient drug treatments. A key feature of pathogenesis, conserved between the human pathogen Mycobacterium tuberculosis and the model pathogen Mycobacterium marinum, is the metabolic switch to lipid catabolism and altered expression of virulence genes at different stages of infection. This study aims to identify genes involved in sustaining viable intracellular infection. We applied transposon sequencing (Tn-Seq) to M. marinum, an unbiased genome-wide strategy combining saturation insertional mutagenesis and high-throughput sequencing. This approach allowed us to identify the localization and relative abundance of insertions in pools of transposon mutants. Gene essentiality and fitness cost of mutations were quantitatively compared between in vitro growth and different stages of infection in two evolutionary distinct phagocytes, the amoeba Dictyostelium discoideum and the murine BV2 microglial cells. In the M. marinum genome, 57% of TA sites were disrupted and 568 genes (10.2%) were essential, which is comparable to previous Tn-Seq studies on M. tuberculosis and M. bovis. Major pathways involved in the survival of M. marinum during infection of D. discoideum are related to DNA damage repair, lipid and vitamin metabolism, the type VII secretion system (T7SS) ESX-1, and the Mce1 lipid transport system. These pathways, except Mce1 and some glycolytic enzymes, were similarly affected in BV2 cells. These differences suggest subtly distinct nutrient availability or requirement in different host cells despite the known predominant use of lipids in both amoeba and microglial cells.IMPORTANCEThe emergence of biochemically and genetically tractable host model organisms for infection studies holds the promise to accelerate the pace of discoveries related to the evolution of innate immunity and the dissection of conserved mechanisms of cell-autonomous defenses. Here, we have used the genetically and biochemically tractable infection model system Dictyostelium discoideum/Mycobacterium marinum to apply a genome-wide transposon-sequencing experimental strategy to reveal comprehensively which mutations confer a fitness advantage or disadvantage during infection and compare these to a similar experiment performed using the murine microglial BV2 cells as host for M. marinum to identify conservation of virulence pathways between hosts.

Transcriptome analysis of the filamentous fungus Aspergillus nidulans directed to the global identification of promoters.

BACKGROUND: The filamentous fungus Aspergillus nidulans has been a tractable model organism for cell biology and genetics for over 60 years. It is among a large number of Aspergilli whose genomes have been sequenced since 2005, including medically and industrially important species. In order to advance our knowledge of its biology and increase its utility as a genetic model by improving gene annotation we sequenced the transcriptome of A. nidulans with a focus on 5' end analysis. RESULTS: Strand-specific whole transcriptome sequencing showed that 80-95% of annotated genes appear to be expressed across the conditions tested. We estimate that the total gene number should be increased by approximately 1000, to 11,800. With respect to splicing 8.3% of genes had multiple alternative transcripts, but alternative splicing by exon-skipping was very rare. 75% of annotated genes showed some level of antisense transcription and for one gene, meaB, we demonstrated the antisense transcript has a regulatory role. Specific sequencing of the 5' ends of transcripts was used for genome wide mapping of transcription start sites, allowing us to interrogate over 7000 promoters and 5' untranslated regions. CONCLUSIONS: Our data has revealed the complexity of the A. nidulans transcriptome and contributed to improved genome annotation. The data can be viewed on the AspGD genome browser.

Fano Resonance in Near-Field Thermal Radiation of Two-Dimensional Van der Waals Heterostructures.

Two-dimensional (2D) materials and their vertically stacked heterostructures have attracted much attention due to their novel optical properties and strong light-matter interactions in the infrared. Here, we present a theoretical study of the near-field thermal radiation of 2D vdW heterostructures vertically stacked of graphene and monolayer polar material (2D hBN as an example). An asymmetric Fano line shape is observed in its near-field thermal radiation spectrum, which is attributed to the interference between the narrowband discrete state (the phonon polaritons in 2D hBN) and a broadband continuum state (the plasmons in graphene), as verified by the coupled oscillator model. In addition, we show that 2D van der Waals heterostructures can achieve nearly the same high radiative heat flux as graphene but with markedly different spectral distributions, especially at high chemical potentials. By tuning the chemical potential of graphene, we can actively control the radiative heat flux of 2D van der Waals heterostructures and manipulate the radiative spectrum, such as the transition from Fano resonance to electromagnetic-induced transparency (EIT). Our results reveal the rich physics and demonstrate the potential of 2D vdW heterostructures for applications in nanoscale thermal management and energy conversion.

Prognostication in Advanced Cancer by Combining Actigraphy-Derived Rest-Activity and Sleep Parameters with Routine Clinical Data: An Exploratory Machine Learning Study.

Survival prediction is integral to oncology and palliative care, yet robust prognostic models remain elusive. We assessed the feasibility of combining actigraphy, sleep diary data, and routine clinical parameters to prognosticate. Fifty adult outpatients with advanced cancer and estimated prognosis of <1 year were recruited. Patients were required to wear an Actiwatch® (wrist actigraph) for 8 days, and complete a sleep diary. Univariate and regularised multivariate regression methods were used to identify predictors from 66 variables and construct predictive models of survival. A total of 49 patients completed the study, and 34 patients died within 1 year. Forty-two patients had disrupted rest-activity rhythms (dichotomy index (I < O ≤ 97.5%) but I < O did not have prognostic value in univariate analyses. The Lasso regularised derived algorithm was optimal and able to differentiate participants with shorter/longer survival (log rank p < 0.0001). Predictors associated with increased survival time were: time of awakening sleep efficiency, subjective sleep quality, clinician's estimate of survival and global health status score, and haemoglobin. A shorter survival time was associated with self-reported sleep disturbance, neutrophil count, serum urea, creatinine, and C-reactive protein. Applying machine learning to actigraphy and sleep data combined with routine clinical data is a promising approach for the development of prognostic tools.

Vitamins D2 and D3 Have Overlapping But Different Effects on the Human Immune System Revealed Through Analysis of the Blood Transcriptome.

Vitamin D is best known for its role in maintaining bone health and calcium homeostasis. However, it also exerts a broad range of extra-skeletal effects on cellular physiology and on the immune system. Vitamins D2 and D3 share a high degree of structural similarity. Functional equivalence in their vitamin D-dependent effects on human physiology is usually assumed but has in fact not been well defined experimentally. In this study we seek to redress the gap in knowledge by undertaking an in-depth examination of changes in the human blood transcriptome following supplementation with physiological doses of vitamin D2 and D3. Our work extends a previously published randomized placebo-controlled trial that recruited healthy white European and South Asian women who were given 15 µg of vitamin D2 or D3 daily over 12 weeks in wintertime in the UK (Nov-Mar) by additionally determining changes in the blood transcriptome over the intervention period using microarrays. An integrated comparison of the results defines both the effect of vitamin D3 or D2 on gene expression, and any influence of ethnic background. An important aspect of this analysis was the focus on the changes in expression from baseline to the 12-week endpoint of treatment within each individual, harnessing the longitudinal design of the study. Whilst overlap in the repertoire of differentially expressed genes was present in the D2 or D3-dependent effects identified, most changes were specific to either one vitamin or the other. The data also pointed to the possibility of ethnic differences in the responses. Notably, following vitamin D3 supplementation, the majority of changes in gene expression reflected a down-regulation in the activity of genes, many encoding pathways of the innate and adaptive immune systems, potentially shifting the immune system to a more tolerogenic status. Surprisingly, gene expression associated with type I and type II interferon activity, critical to the innate response to bacterial and viral infections, differed following supplementation with either vitamin D2 or vitamin D3, with only vitamin D3 having a stimulatory effect. This study suggests that further investigation of the respective physiological roles of vitamin D2 and vitamin D3 is warranted.

Genome analysis of the metabolically versatile Pseudomonas umsongensis GO16: the genetic basis for PET monomer upcycling into polyhydroxyalkanoates.

The throwaway culture related to the single-use materials such as polyethylene terephthalate (PET) has created a major environmental concern. Recycling of PET waste into biodegradable plastic polyhydroxyalkanoate (PHA) creates an opportunity to improve resource efficiency and contribute to a circular economy. We sequenced the genome of Pseudomonas umsongensis GO16 previously shown to convert PET-derived terephthalic acid (TA) into PHA and performed an in-depth genome analysis. GO16 can degrade a range of aromatic substrates in addition to TA, due to the presence of a catabolic plasmid pENK22. The genetic complement required for the degradation of TA via protocatechuate was identified and its functionality was confirmed by transferring the tph operon into Pseudomonas putida KT2440, which is unable to utilize TA naturally. We also identified the genes involved in ethylene glycol (EG) metabolism, the second PET monomer, and validated the capacity of GO16 to use EG as a sole source of carbon and energy. Moreover, GO16 possesses genes for the synthesis of both medium and short chain length PHA and we have demonstrated the capacity of the strain to convert mixed TA and EG into PHA. The metabolic versatility of GO16 highlights the potential of this organism for biotransformations using PET waste as a feedstock.

An inter-laboratory study to investigate the impact of the bioinformatics component on microbiome analysis using mock communities.

Despite the advent of whole genome metagenomics, targeted approaches (such as 16S rRNA gene amplicon sequencing) continue to be valuable for determining the microbial composition of samples. Amplicon microbiome sequencing can be performed on clinical samples from a normally sterile site to determine the aetiology of an infection (usually single pathogen identification) or samples from more complex niches such as human mucosa or environmental samples where multiple microorganisms need to be identified. The methodologies are frequently applied to determine both presence of micro-organisms and their quantity or relative abundance. There are a number of technical steps required to perform microbial community profiling, many of which may have appreciable precision and bias that impacts final results. In order for these methods to be applied with the greatest accuracy, comparative studies across different laboratories are warranted. In this study we explored the impact of the bioinformatic approaches taken in different laboratories on microbiome assessment using 16S rRNA gene amplicon sequencing results. Data were generated from two mock microbial community samples which were amplified using primer sets spanning five different variable regions of 16S rRNA genes. The PCR-sequencing analysis included three technical repeats of the process to determine the repeatability of their methods. Thirteen laboratories participated in the study, and each analysed the same FASTQ files using their choice of pipeline. This study captured the methods used and the resulting sequence annotation and relative abundance output from bioinformatic analyses. Results were compared to digital PCR assessment of the absolute abundance of each target representing each organism in the mock microbial community samples and also to analyses of shotgun metagenome sequence data. This ring trial demonstrates that the choice of bioinformatic analysis pipeline alone can result in different estimations of the composition of the microbiome when using 16S rRNA gene amplicon sequencing data. The study observed differences in terms of both presence and abundance of organisms and provides a resource for ensuring reproducible pipeline development and application. The observed differences were especially prevalent when using custom databases and applying high stringency operational taxonomic unit (OTU) cut-off limits. In order to apply sequencing approaches with greater accuracy, the impact of different analytical steps needs to be clearly delineated and solutions devised to harmonise microbiome analysis results.

Genetic screening for the protective antigenic targets of BCG vaccination.

Bovine tuberculosis is an important animal health problem and the predominant cause of zoonotic tuberculosis worldwide. It results in serious economic burden due to losses in productivity and the cost of control programmes. Control could be greatly improved by the introduction of an efficacious cattle vaccine but the most likely candidate, BCG, has several limitations including variable efficacy. Augmentation of BCG with a subunit vaccine booster has been shown to increase protection but the selection of antigens has hitherto been left largely to serendipity. In the present study, we take a rational approach to identify the protective antigens of BCG, selecting a BCG transposon mutant library in naïve and BCG-vaccinated cattle. Ten mutants had increased relative survival in vaccinated compared to naïve cattle, consistent with loss of protective antigen targets making the mutants less visible to the BCG immune response. The immunogenicity of three putative protective antigens, BCG_0116, BCG_0205 (YrbE1B) and BCG_1448 (PPE20) was investigated using peptide pools and PBMCs from BCG vaccinated cattle. BCG vaccination induced PBMC to release elevated levels of IP10, IL-17a and IL-10 in response to all three antigens. Taken together, the data supports the further study of these antigens for use in subunit vaccines.

GSMN-ML- a genome scale metabolic network reconstruction of the obligate human pathogen Mycobacterium leprae.

Leprosy, caused by Mycobacterium leprae, has plagued humanity for thousands of years and continues to cause morbidity, disability and stigmatization in two to three million people today. Although effective treatment is available, the disease incidence has remained approximately constant for decades so new approaches, such as vaccine or new drugs, are urgently needed for control. Research is however hampered by the pathogen's obligate intracellular lifestyle and the fact that it has never been grown in vitro. Consequently, despite the availability of its complete genome sequence, fundamental questions regarding the biology of the pathogen, such as its metabolism, remain largely unexplored. In order to explore the metabolism of the leprosy bacillus with a long-term aim of developing a medium to grow the pathogen in vitro, we reconstructed an in silico genome scale metabolic model of the bacillus, GSMN-ML. The model was used to explore the growth and biomass production capabilities of the pathogen with a range of nutrient sources, such as amino acids, glucose, glycerol and metabolic intermediates. We also used the model to analyze RNA-seq data from M. leprae grown in mouse foot pads, and performed Differential Producibility Analysis to identify metabolic pathways that appear to be active during intracellular growth of the pathogen, which included pathways for central carbon metabolism, co-factor, lipids, amino acids, nucleotides and cell wall synthesis. The GSMN-ML model is thereby a useful in silico tool that can be used to explore the metabolism of the leprosy bacillus, analyze functional genomic experimental data, generate predictions of nutrients required for growth of the bacillus in vitro and identify novel drug targets.