The atypical two-component system (TCS) AbrC1/C2/C3 (encoded by SCO4598, SCO4597, and SCO4596), comprising two histidine kinases (HKs) and a response regulator (RR), is crucial for antibiotic production in Streptomyces coelicolor and for morphological differentiation under certain nutritional conditions. In this study, we demonstrate that deletion of the RR-encoding gene, abrC3 (SCO4596), results in a dramatic decrease in actinorhodin (ACT) and undecylprodiginine (RED) production and delays morphological development. In contrast, the overexpression of abrC3 in the parent strain leads to a 33% increase in ACT production in liquid medium. Transcriptomic analysis and chromatin immunoprecipitation with microarray technology (ChIP-chip) analysis of the abrC3 mutant and the parent strain revealed that AbrC3 directly controls ACT production by binding to the actII-ORF4 promoter region; this was independently verified by in vitro DNA-binding assays. This binding is dependent on the sequence 5'-GAASGSGRMS-3'. In contrast, the regulation of RED production is not due to direct binding of AbrC3 to either the redZ or redD promoter region. This study also revealed other members of the AbrC3 regulon: AbrC3 is a positive autoregulator which also binds to the promoter regions of SCO0736, bdtA (SCO3328), absR1 (SCO6992), and SCO6809. The direct targets share the 10-base consensus binding sequence and may be responsible for some of the phenotypes of the abrC3 mutant. The identification of the AbrC3 regulon as part of the complex regulatory network governing antibiotic production widens our knowledge regarding TCS involvement in control of antibiotic synthesis and may contribute to the rational design of new hyperproducer host strains through genetic manipulation of such systems.
Wagley S, Newcombe J, Laing E, Yusuf E, Sambles CM, Studholme DJ, La Ragione RM, Titball RW, Champion OL (2014) Differences in carbon source utilisation distinguish Campylobacter jejuni from Campylobacter coli., BMC Microbiol 14
BACKGROUND: Campylobacter jejuni and C. coli are human intestinal pathogens that are the most frequent causes of bacterial foodborne gastroenteritis in humans in the UK. In this study, we aimed to characterise the metabolic diversity of both C. jejuni and C. coli using a diverse panel of clinical strains isolated from the UK, Pakistan and Thailand, thereby representing both the developed and developing world. Our aim was to apply multi genome analysis and Biolog phenotyping to determine differences in carbon source utilisation by C. jejuni and C. coli strains. RESULTS: We have identified a core set of carbon sources (utilised by all strains tested) and a set that are differentially utilised for a diverse panel of thirteen C. jejuni and two C. coli strains. This study used multi genome analysis to show that propionic acid is utilised only by C. coli strains tested. A broader PCR screen of 16 C. coli strains and 42 C. jejuni confirmed the absence of the genes needed for propanoate metabolism. CONCLUSIONS: From our analysis we have identified a phenotypic method and two genotypic methods based on propionic utilisation that might be applicable for distinguishing between C. jejuni and C. coli.
Lordan J, Karanjia N, Bucca G, Laing E, Smith C (2010) Prospective analysis of the gene expression signature of peri-metastasis 'halo' tissue following neo-adjuvant chemotherapy-induced tumour reduction of colorectal liver metastasis, BRITISH JOURNAL OF SURGERY 97 pp. 61-62 WILEY-BLACKWELL
Möller-Levet CS, Archer SN, Bucca G, Laing EE, Slak A, Kabiljo R, Lo JC, Santhi N, von Schantz M, Smith CP, Dijk DJ (2013) Effects of insufficient sleep on circadian rhythmicity and expression amplitude of the human blood transcriptome., Proc Natl Acad Sci U S A 110 (12) pp. E1132-E1141
Insufficient sleep and circadian rhythm disruption are associated with negative health outcomes, including obesity, cardiovascular disease, and cognitive impairment, but the mechanisms involved remain largely unexplored. Twenty-six participants were exposed to 1 wk of insufficient sleep (sleep-restriction condition 5.70 h, SEM = 0.03 sleep per 24 h) and 1 wk of sufficient sleep (control condition 8.50 h sleep, SEM = 0.11). Immediately following each condition, 10 whole-blood RNA samples were collected from each participant, while controlling for the effects of light, activity, and food, during a period of total sleep deprivation. Transcriptome analysis revealed that 711 genes were up- or down-regulated by insufficient sleep. Insufficient sleep also reduced the number of genes with a circadian expression profile from 1,855 to 1,481, reduced the circadian amplitude of these genes, and led to an increase in the number of genes that responded to subsequent total sleep deprivation from 122 to 856. Genes affected by insufficient sleep were associated with circadian rhythms (PER1, PER2, PER3, CRY2, CLOCK, NR1D1, NR1D2, RORA, DEC1, CSNK1E), sleep homeostasis (IL6, STAT3, KCNV2, CAMK2D), oxidative stress (PRDX2, PRDX5), and metabolism (SLC2A3, SLC2A5, GHRL, ABCA1). Biological processes affected included chromatin modification, gene-expression regulation, macromolecular metabolism, and inflammatory, immune and stress responses. Thus, insufficient sleep affects the human blood transcriptome, disrupts its circadian regulation, and intensifies the effects of acute total sleep deprivation. The identified biological processes may be involved with the negative effects of sleep loss on health, and highlight the interrelatedness of sleep homeostasis, circadian rhythmicity, and metabolism.
Swiatek MA, Gubbens J, Bucca G, Song E, Yang YH, Laing E, Kim BG, Smith CP, van Wezel GP (2013) The ROK-family regulator Rok7B7 pleiotropicaly affects xylose utilization, carbon catabolite repression and antibiotic production in Streptomyces coelicolor., J Bacteriol 195 (6) pp. 1236-1248
American Society for Microbiology
Members of the ROK family of proteins are mostly transcriptional regulators and kinases that generally relate to the control of primary metabolism, whereby its member glucose kinase acts as the central control protein in carbon control in Streptomyces. Here we show that deletion of SCO6008 (rok7B7) strongly affects carbon catabolite repression (CCR), growth and antibiotic production in Streptomyces coelicolor. Deletion of SCO7543 also affected antibiotic production, while no major changes were observed after deletion of the rok family genes SCO0794, SCO1060, SCO2846, SCO6566 or SCO6600. Global expression profiling of the rok7B7 mutant by proteomics and microarray analysis revealed strong up-regulation of the xylose transporter operon xylFGH, which lies immediately downstream of rok7B7, consistent with the improved growth and delayed development of the mutant on xylose. The enhanced CCR, which was especially obvious on rich or xylose-containing media, correlated with elevated expression of glucose kinase and of the glucose transporter GlcP. In liquid-grown cultures, expression of the biosynthetic enzymes for production of prodigionines (Red), siderophores and calcium dependent antibiotic (Cda) was enhanced in the mutant, and overproduction of Red was corroborated by MALDI-ToF analysis. These data present Rok7B7 as a pleiotropic regulator of growth, CCR and antibiotic production in Streptomyces.
Archer SN, Laing EE, Moeller-Levet CS, van der Veen DR, Bucca G, Lazar AS, Santhi N, Slak A, Kabiljo R, von Schantz M, Smith CP, Dijk D-J (2014) Mistimed sleep disrupts circadian regulation of the human transcriptome, PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA 111 (6) pp. E682-E691
We performed a pilot study, looking at the COX-2 inhibitor celecoxib, on newly diagnosed prostate cancer patients in the neo-adjuvant setting using DNA microarray analysis.
Thomas SA, Jin Y, Laing E, Smith CP (2013) Reconstructing regulatory networks in Streptomyces using evolutionary algorithms, 2013 13th UK Workshop on Computational Intelligence, UKCI 2013 pp. 24-30
Reconstructing biological networks is vital in developing our understanding of nature. Biological systems of particular interest are bacteria that can produce antibiotics during their life cycle. Such an organism is the soil dwelling bacterium Streptomyces coelicolor. Although some of the genes involved in the production of antibiotics in the bacterium have been identified, how these genes are regulated and their specific role in antibiotic production is unknown. By understanding the network structure and gene regulation involved it may be possible to improve the production of antibiotics from this bacterium. Here we use an evolutionary algorithm to optimise parameters in the gene regulatory network of a sub-set of genes in S. coelicolor involved in antibiotic production. We present some of our preliminary results based on real gene expression data for continuous and discrete modelling techniques. © 2013 IEEE.
Archer SN, Laing EE, Möller-Levet CS, van der Veen DR, Bucca G, Lazar AS, Santhi N, Slak A, Kabiljo R, von Schantz M, Smith CP, Dijk DJ (2014) Mistimed sleep disrupts circadian regulation of the human transcriptome., Proc Natl Acad Sci U S A
Circadian organization of the mammalian transcriptome is achieved by rhythmic recruitment of key modifiers of chromatin structure and transcriptional and translational processes. These rhythmic processes, together with posttranslational modification, constitute circadian oscillators in the brain and peripheral tissues, which drive rhythms in physiology and behavior, including the sleep-wake cycle. In humans, sleep is normally timed to occur during the biological night, when body temperature is low and melatonin is synthesized. Desynchrony of sleep-wake timing and other circadian rhythms, such as occurs in shift work and jet lag, is associated with disruption of rhythmicity in physiology and endocrinology. However, to what extent mistimed sleep affects the molecular regulators of circadian rhythmicity remains to be established. Here, we show that mistimed sleep leads to a reduction of rhythmic transcripts in the human blood transcriptome from 6.4% at baseline to 1.0% during forced desynchrony of sleep and centrally driven circadian rhythms. Transcripts affected are key regulators of gene expression, including those associated with chromatin modification (methylases and acetylases), transcription (RNA polymerase II), translation (ribosomal proteins, initiation, and elongation factors), temperature-regulated transcription (cold inducible RNA-binding proteins), and core clock genes including CLOCK and ARNTL (BMAL1). We also estimated the separate contribution of sleep and circadian rhythmicity and found that the sleep-wake cycle coordinates the timing of transcription and translation in particular. The data show that mistimed sleep affects molecular processes at the core of circadian rhythm generation and imply that appropriate timing of sleep contributes significantly to the overall temporal organization of the human transcriptome.
Thomas SA, jin Y, Laing E, Smith CP (2016) Modeling Dynamic Gene Expression in Streptomyces Coelicolor: Comparing Single and Multi-Objective Setups, In: Iba H, Noman N (eds.), Evolutionary Computation in Gene Regulatory Network Research 7 John Wiley & Sons
"This book is a step-by-step guideline for research in gene regulatory networks (GRN) using evolutionary computation (EC)"-- This book serves as a handbook for gene regulatory network research using evolutionary algorithms, with ...
Streptomycetes sense and respond to the stress of phosphate starvation via the two-component PhoR-PhoP signal transduction system. To identify the in vivo targets of PhoP we have undertaken a chromatin-immunoprecipitation-on-microarray analysis of wild-type and phoP mutant cultures and, in parallel, have quantified their transcriptomes. Most (ca. 80%) of the previously in vitro characterized PhoP targets were identified in this study among several hundred other putative novel PhoP targets. In addition to activating genes for phosphate scavenging systems PhoP was shown to target two gene clusters for cell wall/extracellular polymer biosynthesis. Furthermore PhoP was found to repress an unprecedented range of pathways upon entering phosphate limitation including nitrogen assimilation, oxidative phosphorylation, nucleotide biosynthesis and glycogen catabolism. Moreover, PhoP was shown to target many key genes involved in antibiotic production and morphological differentiation, including afsS, atrA, bldA, bldC, bldD, bldK, bldM, cdaR, cdgA, cdgB and scbR-scbA. Intriguingly, in the PhoP-dependent cpk polyketide gene cluster, PhoP accumulates substantially at three specific sites within the giant polyketide synthase-encoding genes. This study suggests that, following phosphate limitation, Streptomyces coelicolor PhoP functions as a 'master' regulator, suppressing central metabolism, secondary metabolism and developmental pathways until sufficient phosphate is salvaged to support further growth and, ultimately, morphological development.
The sporulation of aerial hyphae of Streptomyces coelicolor is a complex developmental process. Only a limited number of the genes involved in this intriguing morphological differentiation programme are known, including some key regulatory genes. The aim of this study was to expand our knowledge of the gene repertoire involved in S. coelicolor sporulation.
Streptomycetes produce a wealth of natural products, including over half of all known antibiotics. It was previously demonstrated that N-acetylglucosamine and secondary metabolism are closely entwined in streptomycetes. Here we show that DNA recognition by the N-acetylglucosamine-responsive regulator DasR is growth-phase dependent, and that DasR can bind to sites in the S. coelicolor genome that have no obvious resemblance to previously identified DasR-responsive elements. Thus, the regulon of DasR extends well beyond what was previously predicted and includes a large number of genes with functions far removed from N-acetylglucosamine metabolism, such as genes for small RNAs and DNA transposases. Conversely, the DasR regulon during vegetative growth largely correlates to the presence of canonical DasR-responsive elements. The changes in DasR binding in vivo following N-acetylglucosamine induction were studied in detail and a possible molecular mechanism by which the influence of DasR is extended is discussed. Discussion of DasR binding was further informed by a parallel transcriptome analysis of the respective cultures. Evidence is provided that DasR binds directly to the promoters of all genes encoding pathway-specific regulators of antibiotic production in S. coelicolor, thereby providing an exquisitely simple link between nutritional control and secondary metabolism.
Noens EE, Mersinias V, Willemse J, Traag BA, Laing E, Chater KF, Smith CP, Koerten HK, van Wezel GP (2007) Loss of the controlled localization of growth stage-specific cell-wall synthesis pleiotropically affects developmental gene expression in an ssgA mutant of Streptomyces coelicolor, MOLECULAR MICROBIOLOGY 64 (5) pp. 1244-1259 BLACKWELL PUBLISHING
Romero DA, Hasan AH, Lin YF, Kime L, Ruiz-Larrabeiti O, Urem M, Bucca G, Mamanova L, Laing EE, van Wezel GP, Smith CP, Kaberdin VR, McDowall KJ (2014) A comparison of key aspects of gene regulation in Streptomyces coelicolor and Escherichia coli using nucleotide-resolution transcription maps produced in parallel by global and differential RNA sequencing., Mol Microbiol
Streptomyces coelicolor is a model for studying bacteria renowned as the foremost source of natural products used clinically. Post-genomic studies have revealed complex patterns of gene expression and links to growth, morphological development and individual genes. However, the underlying regulation remains largely obscure, but undoubtedly involves steps after transcription initiation. Here we identify sites involved in RNA processing and degradation as well as transcription within a nucleotide-resolution map of the transcriptional landscape. This was achieved by combining RNA-sequencing approaches suited to the analysis of GC-rich organisms. Escherichia coli was analysed in parallel to validate the methodology and allow comparison. Previously, sites of RNA processing and degradation had not been mapped on a transcriptome-wide scale for E. coli. Through examples, we show the value of our approach and data sets. This includes the identification of new layers of transcriptional complexity associated with several key regulators of secondary metabolism and morphological development in S. coelicolor and the identification of host-encoded leaderless mRNA and rRNA processing associated with the generation of specialized ribosomes in E. coli. New regulatory small RNAs were identified for both organisms. Overall the results illustrate the diversity in mechanisms used by different bacterial groups to facilitate and regulate gene expression.
Archer SN, Laing EE, Moller-Levet CS, van der Veen DR, Bucca G, Lazar AS, Lo JCY, Santhi N, Slak A, Kabiljo R, von Schantz M, Smith CP, Dijk DJ (2014) Mistimed sleep disrupts the circadian regulation of the human transcriptome, JOURNAL OF SLEEP RESEARCH 23 pp. 15-15 WILEY-BLACKWELL
RNA-binding proteins (RBPs) are essential for post-transcriptional regulation of gene expression. Recent high-throughput screens have dramatically increased the number of experimentally identified RBPs; however, comprehensive identification of RBPs within living organisms is elusive. Here we describe the repertoire of 765 and 594 proteins that reproducibly interact with polyadenylated mRNAs in Saccharomyces cerevisiae and Caenorhabditis elegans, respectively. Furthermore, we report the differential association of mRNA-binding proteins (mRPBs) upon induction of apoptosis in C. elegans L4-stage larvae. Strikingly, most proteins composing mRBPomes, including components of early metabolic pathways and the proteasome, are evolutionarily conserved between yeast and C. elegans. We speculate, on the basis of our evidence that glycolytic enzymes bind distinct glycolytic mRNAs, that enzyme-mRNA interactions relate to an ancient mechanism for post-transcriptional coordination of metabolic pathways that perhaps was established during the transition from the early 'RNA world' to the 'protein world'.
Tellez JO, Dobrzynski H, Greener ID, Graham GM, Laing E, Honjo H, Hubbard SJ, Boyett MR, Billeter R (2006) Differential expression of ion channel transcripts in atrial muscle and sinoatrial node in rabbit, CIRCULATION RESEARCH 99 (12) pp. 1384-1393 LIPPINCOTT WILLIAMS & WILKINS
Laing EE, Johnston JD, Möller-Levet CS, Bucca G, Smith CP, Dijk DJ, Archer SN (2015) Exploiting human and mouse transcriptomic data: Identification of circadian genes and pathways influencing health, BioEssays 37 (5) pp. 544-556
© 2015 The Authors. Bioessays published by WILEY Periodicals, Inc.The power of the application of bioinformatics across multiple publicly available transcriptomic data sets was explored. Using 19 human and mouse circadian transcriptomic data sets, we found that NR1D1 and NR1D2 which encode heme-responsive nuclear receptors are the most rhythmic transcripts across sleep conditions and tissues suggesting that they are at the core of circadian rhythm generation. Analyzes of human transcriptomic data show that a core set of transcripts related to processes including immune function, glucocorticoid signalling, and lipid metabolism is rhythmically expressed independently of the sleep-wake cycle. We also identify key transcripts associated with transcription and translation that are disrupted by sleep manipulations, and through network analysis identify putative mechanisms underlying the adverse health outcomes associated with sleep disruption, such as diabetes and cancer. Comparative bioinformatics applied to existing and future data sets will be a powerful tool for the identification of core circadian- and sleep-dependent molecules.
Salerno P, Larsson J, Bucca G, Laing E, Smith CP, Flardh K (2009) One of the Two Genes Encoding Nucleoid-Associated HU Proteins in Streptomyces coelicolor Is Developmentally Regulated and Specifically Involved in Spore Maturation, J BACTERIOL 191 (21) pp. 6489-6500 AMER SOC MICROBIOLOGY
Streptomyces genomes encode two homologs of the nucleoid-associated HU proteins. One of them, here designated HupA, is of a conventional type similar to E. coli HU and HU , while the other, HupS, is a two-domain protein. In addition to the N-terminal part that is similar to that of HU proteins, it has a C-terminal domain that is similar to the alanine- and lysine-rich C termini of eukaryotic linker histones. Such
two-domain HU proteins are found only among Actinobacteria. In this phylum some organisms have only a single HU protein of the type with a C-terminal histone H1-like domain (e.g., Hlp in Mycobacterium smegmatis), while others have only a single conventional HU. Yet others, including the streptomycetes, produce both types of HU proteins. We show here that the two HU genes in Streptomyces coelicolor are differentially regulated and that hupS is specifically expressed during sporulation, while hupA is expressed in vegetative hyphae. The
developmental upregulation of hupS occurred in sporogenic aerial hyphal compartments and was dependent on the developmental regulators whiA, whiG, and whiI. HupS was found to be nucleoid associated in spores, and a hupS deletion mutant had an average nucleoid size in spores larger than that in the parent strain. The mutant
spores were also defective in heat resistance and spore pigmentation, although they possessed apparently normal spore walls and displayed no increased sensitivity to detergents. Overall, the results show that HupS is specifically involved in sporulation and may affect nucleoid architecture and protection in spores of S.
In humans, a primate-specific variable-number tandem-repeat (VNTR) polymorphism (4 or 5 repeats 54 nt in length) in the circadian gene PER3 is associated with differences in sleep timing and homeostatic responses to sleep loss. We investigated the effects of this polymorphism on circadian rhythmicity and sleep homeostasis by introducing the polymorphism into mice and assessing circadian and sleep parameters at baseline and during and after 12 h of sleep deprivation (SD). Microarray analysis was used to measure hypothalamic and cortical gene expression. Circadian behavior and sleep were normal at baseline. The response to SD of 2 electrophysiological markers of sleep homeostasis, electroencephalography (EEG) ¸ power during wakefulness and ´ power during sleep, were greater in the Per3(5/5) mice. During recovery, the Per3(5/5) mice fully compensated for the SD-induced deficit in ´ power, but the Per3(4/4) and wild-type mice did not. Sleep homeostasis-related transcripts (e.g., Homer1, Ptgs2, and Kcna2) were differentially expressed between the humanized mice, but circadian clock genes were not. These data are in accordance with the hypothesis derived from human data that the PER3 VNTR polymorphism modifies the sleep homeostatic response without significantly influencing circadian parameters.-Hasan, S., van der Veen, D. R., Winsky-Sommerer, R., Hogben, A., Laing, E. E., Koentgen, F., Dijk, D.-J., Archer, S. N. A human sleep homeostasis phenotype in mice expressing a primate-specific PER3 variable-number tandem-repeat coding-region polymorphism.
Rahman T, Mahapatra M, Laing E, Jin Y (2014) Evolutionary non-linear modelling for selecting vaccines against antigenically variable viruses., Bioinformatics 31 (6) pp. 834-840
MOTIVATION: In vitro and in vivo selection of vaccines is time consuming, expensive and the selected vaccines may not be able to provide protection against broad-spectrum viruses because of emerging antigenically novel disease strains. A powerful computational model that incorporates these protein/DNA or RNA level fluctuations can effectively predict antigenically variant strains, and can minimize the amount of resources spent on exclusive serological testing of vaccines and make wide spectrum vaccines possible for many diseases. However, in silico vaccine prediction remains a grand challenge. To address the challenge, we investigate the use of linear and non-linear regression models to predict the antigenic similarity in foot-and-mouth disease virus strains and in influenza strains, where the structure and parameters of the non-linear model are optimized using an evolutionary algorithm (EA). In addition, we examine two different scoring methods for weighting the type of amino acid substitutions in the linear and non-linear models. We also test our models with some unseen data. RESULTS: We achieved the best prediction results on three datasets of SAT2 (Foot-and-Mouth disease), two datasets of serotype A (Foot-and-Mouth disease) and two datasets of influenza when the scoring method based on biochemical properties of amino acids is employed in combination with a non-linear regression model. Models based on substitutions in the antigenic areas performed better than those that took the entire exposed viral capsid proteins. A majority of the non-linear regression models optimi Z: ed with the EA: performed better than the linear and non-linear models whose parameters are estimated using the least-squares method. In addition, for the best models, optimi Z: ed non-linear regression models consist of more terms than their linear counterparts, implying a non-linear nature of influences of amino acid substitutions. Our models were also tested on five recently generated FMDV datasets and the best model was able to achieve an 80% agreement rate.
The power of the application of bioinformatics across multiple publicly available transcriptomic data sets was explored. Using 19 human and mouse circadian transcriptomic data sets, we found that NR1D1 and NR1D2 which encode heme-responsive nuclear receptors are the most rhythmic transcripts across sleep conditions and tissues suggesting that they are at the core of circadian rhythm generation. Analyzes of human transcriptomic data show that a core set of transcripts related to processes including immune function, glucocorticoid signalling, and lipid metabolism is rhythmically expressed independently of the sleep-wake cycle. We also identify key transcripts associated with transcription and translation that are disrupted by sleep manipulations, and through network analysis identify putative mechanisms underlying the adverse health outcomes associated with sleep disruption, such as diabetes and cancer. Comparative bioinformatics applied to existing and future data sets will be a powerful tool for the identification of core circadian- and sleep-dependent molecules.
Diagnosis and treatment of circadian rhythm sleep-wake disorders requires assessment of circadian phase of the brain?s circadian pacemaker. The gold-standard univariate method is based on collection of a 24 h time series of plasma melatonin, a suprachiasmatic nucleus driven pineal hormone. We developed and validated a multivariate whole-blood mRNA based predictor of melatonin phase which requires few samples. Transcriptome data were collected under normal, sleep-deprivation and abnormal sleep-timing conditions to assess robustness of the predictor. Partial least square regression (PLSR), applied to the transcriptome, identified a set of 100 biomarkers primarily related to glucocorticoid signaling and immune function. Validation showed that PLSR-based predictors outperform published blood-derived circadian phase predictors. When given one sample as input, the R2 of predicted vs observed phase was 0.74, whereas for two samples taken 12 h apart, R2 was 0.90. This blood transcriptome based model enables assessment of circadian phase from a few samples.
Campylobacter is the most common cause of bacterial gastroenteritis in the developed world, with approximately 70,000 cases reported in the UK per annum. It is well accepted that Campylobacter spp. form biofilms which aid its survival in both the environment and the host. The formation of biofilms in poultry processing plants are of particular concern, as they are potential sources of contamination between meat batches, and facilitate the transmission of the pathogen through the human food chain. However, despite the importance of biofilms, the molecular mechanisms and metabolic pathways associated with biofilm formation in Campylobacter have not been well elucidated.
Here, 30 C. jejuni strains were isolated from commercial chicken meat and assayed for their motility and ability to form biofilms, using crystal violet staining at 37RC and 42RC. Only five of the 30 isolates were able to form biofilms, with more complex biofilm phenotypes observed at 37RC. Although all isolates were motile, a weak correlation between motility and biofilm formation was observed, indicating that motility is not essential to the phenotype. Ten isolates were selected, representing the five most competent, and five poorest biofilm formers. These isolates were screened for their virulence profiles using Galleria mellonella and adhesion and invasion of Caco-2 models. No correlation between the ability to form biofilms and virulence phenotypes was observed.
A competent biofilm former (isolate CJP13) was selected and a mariner transposon mutant library was constructed in this strain. Over 3,000 of the resulting transposon mutants were individually screened for their ability to form biofilms. Thirteen of the 3,000 transposon mutants showed reduced ability to form biofilms across two independent biological replicates. Of those, individual knock-out mutants of Cj0080, Cj1623 (memP), hydA and trbJ and complemented mutants were constructed in CJP13 and NCTC11168 strains. All mutants showed reduced ability to form biofilms compared to wild type strains, although the NCTC11168 memP mutant showed the most significant reduction, with almost no biofilm ability observed (p
Next-Generation Sequencing (NGS) and subsequent pangenome analysis revealed genes which were differentially present/absent in competent and poor biofilm genomes, two of which are involved with sialic acid synthesis and transport. Phylogenetic analysis revealed CJP17 and CJP19 strains (competent and poor biofilm formers respectively) to be almost genetically identical, with three gene mutations in the CJP17 genome. One such mutation is predicted to cause truncation of pflA, which is suggested to be the cause of reduced motility in this strain compared to CJP19. Despite this mutation, CJP17 displayed a competent biofilm phenotype, suggesting the mechanisms involved in biofilm formation are motility independent.
The panel of 10 isolates were subjected to Biolog phenotypic array analysis to study the ability of Campylobacter to metabolise 95 different carbon substrates. Competent biofilm formers were able to significantly metabolise several carbon sources more readily; D-ribose and L-lyxose when using lag phase to define utilisation, and L-lactic acid when using max utilisation and max slope to represent substrate utilisation parameters. However, varying concentrations of L-lactic acid failed to induce biofilm formation in chicken isolates when added to complex media.
The studies reported here demonstrate significant differences in the metabolism and genetic composition between poor and competent biofilm isolates. Moreover, this work provides evidence that multiple C. jejuni genes are responsible for the biofilm phenotype in currently circulating C. jejuni isolates. This study suggests that the role of membrane proteins, such as memP, is key in the formation of biofilm in NCTC11168, but les
In vitro and in vivo selection of vaccines is time consuming, expensive and the selected vaccines
may not be able to provide protection against broad-spectrum viruses owing to the complexities
of emerging antigenically novel disease strains. A powerful computational model that can
effectively predict antigenically variant strains can minimise the amount of resources spent
on exclusive serological testing of vaccines and make broad spectrum vaccines possible for
many diseases. However, in silico vaccine prediction remains a grand challenge. To address
this challenge, we investigate the use of linear regression, non-linear regression and support
vector machine (SVM) classification models to predict the antigenic similarity between footand-
mouth disease virus (FMDV) strains. The parameters of the linear regression model are
estimated using the least squares method and the structure and parameters of the non-linear
model are optimised using a hybrid evolutionary algorithm. We apply semi-supervised classification
methods i.e. transductive SVM (TSVM) to improve our classification results due to the
availability of limited labelled data. In addition, we examine two different scoring methods for
weighting the type of amino acid substitutions in the classification and regression models in two
different setups i.e. the entire external viral capsid protein or only antigenically important areas
in the capsid proteins are considered.
Statistical analysis of our data confirmed possible correlates of amino acid substitutions in
antigenic areas in capsid proteins of FMDV and influenza. Across all our prediction models, we
achieved the best results when the scoring method based on biochemical properties of amino
acids is employed in combination with regression or classification and models based on substitutions
in the antigenic areas performed better than those that took the entire exposed viral capsid
protein. In our regression analysis, the non-linear regression method optimised with the evolutionary
algorithm performed consistently better (throughout FMDV and influenza datasets)
than the linear and non-linear models whose parameters are estimated using the least squares
method. In addition, for the best models, optimised non-linear regression models consist of
more terms than their linear counterparts, implying a non-linear nature of influences of amino
acid substitutions. For our classification models we also used Ebola data. Our TSVM models
outperformed our SVM models across all datasets i.e. FMDV, influenza and Ebola, which confirmed
the benefits of using unlabelled data for boosting generalization performance. However,
including additional antigenic areas in our Ebola TSVM model had no effect on the prediction
ability of the model which we think is because the additional peptides were not biologically
significant in terms of relaying any effect on the antigenic values which we use as our labels.
Stress-induced adaptations requiremultiple levels of
regulation in all organisms to repair cellular damage.
In the present study we evaluated the genome-wide
transcriptional and translational changes following
heat stress exposure in the soil-dwelling model actinomycete
bacterium, Streptomyces coelicolor. The
combined analysis revealed an unprecedented level
of translational control of gene expression, deduced
through polysome profiling, in addition to transcriptional
changes. Our data show little correlation between
the transcriptome and ?translatome?; while an
obvious downward trend in genome wide transcription
was observed, polysome associated transcripts
following heat-shock showed an opposite upward
trend. A handful of key protein players, including
the major molecular chaperones and proteases were
highly induced at both the transcriptional and translational
level following heat-shock, a phenomenon
known as ?potentiation?. Many other transcripts encoding
cold-shock proteins, ABC-transporter systems,
multiple transcription factors weremore highly
polysome-associated following heat stress; interestingly,
these protein families were not induced at the
transcriptional level and therefore were not previously
identified as part of the stress response. Thus,
stress coping mechanisms at the level of gene expression
in this bacterium go well beyond the induction
of a relatively small number of molecular chaperones
and proteases in order to ensure cellular survival
at non-physiological temperatures.
Acute and chronic insufficient sleep are associated with adverse health outcomes and risk of accidents.
There is therefore a need for biomarkers to monitor sleep debt status. None are currently available. We
applied Elastic-net and Ridge regression to entire and pre-filtered transcriptome samples collected in
healthy young adults during acute total sleep deprivation and following 1 week of either chronic
status. The size of identified panels ranged from 9-74 biomarkers. Panel performance, assessed by
leave-one-subject-out cross-validation and independent validation, varied between sleep debt
conditions. Using between-subject assessments based on one blood sample, the accuracy of classifying
?Acute sleep loss? was 92%, but only 57% for classifying ?Chronic sleep insufficiency?. A reasonable
accuracy for classifying ?chronic sleep insufficiency? could only be achieved by a within-subject
comparison of blood samples. Biomarkers for sleep debt status showed little overlap with previously
identified biomarkers for circadian phase. Biomarkers for acute and chronic sleep loss also showed little
overlap but were associated with common functions related to the cellular stress response, such as heat
shock protein activity, the unfolded protein response, protein ubiquitination and endoplasmic reticulum
associated protein degradation, and apoptosis. This characteristic response of whole blood to sleep loss
can further aid our understanding of how sleep insufficiencies negatively affect health. Further
development of these novel biomarkers for research and clinical practice requires validation in other
protocols and age groups.
Nollet Mathieu, Hicks Harriet, McCarthy Andrew P., Wu Huihai, Moller-Levet Carla S., Laing Emma E., Malki Karim, Lawless Nathan, Wafford Keith A., Dijk Derk-Jan, Winsky-Sommerer Raphaelle (2019) REM sleep: unique associations with corticosterone regulation, apoptotic pathways and behavior in chronic stress in mice, Proceedings of the National Academy of Sciences 116 (7) pp. 2733-2742
National Academy of Sciences of the United States of America
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 nine weeks of unpredictable chronic mild stress (UCMS). Comparing 46 phenotypical 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 which were enriched in 193 pathways, including some involved in stem cells, immune response, apoptosis and survival. Only 3 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.
Christou Skevoulla, Wehrens Sophie M T, Isherwood Cheryl, Moller-Levet Carla S, Wu Huihai, Revell Victoria L, Bucca Giselda, Skene Debra J, Laing Emma E, Archer Simon N, Johnston Jonathan D (2019) Circadian regulation in human white adipose tissue revealed by transcriptome and metabolic network analysis, Scientific Reports
Studying circadian rhythms in most human tissues is hampered by difficulty in collecting serial samples. Here we reveal circadian rhythms in the transcriptome and metabolic pathways of human white adipose tissue. Subcutaneous adipose tissue was taken from seven healthy males under highly controlled ?constant routine? conditions. Five biopsies per participant were taken at six-hourly intervals for microarray analysis and in silico integrative metabolic modelling. We identified 837 transcripts exhibiting circadian expression profiles (2% of 41619 transcript targeting probes on the array), with clear separation of transcripts peaking in the morning (258 probes) and evening (579 probes). There was only partial overlap of our rhythmic transcripts with published animal adipose and human blood transcriptome data. Morning-peaking transcripts associated with regulation of gene expression, nitrogen compound metabolism, and nucleic acid biology; evening-peaking transcripts associated with organic acid metabolism, cofactor metabolism and redox activity. In silico pathway analysis further indicated circadian regulation of lipid and nucleic acid metabolism; it also predicted circadian variation in key metabolic pathways such as the citric acid cycle and branched chain amino acid degradation. In summary, in vivo circadian rhythms exist in multiple adipose metabolic pathways, including those involved in lipid metabolism, and core aspects of cellular biochemistry.
The DNA microarray is a high throughput technology that is able to scan thousands of genes simultaneously and read their expression level. However, there are many challenges associated with data. One of the main opportunities is the curse of dimensionality which makes it difficult to learn without overfitting. Therefore, we proposed an unsupervised nonlinear machine learning framework to explore the circadian rhythmic features as a case study. Auto-encoder is capable of automatically learn the microarray data features and reveal knowledge that can help in designing the complex relations between the features for a circadian disorder in the future. Features derived from unsupervised algorithms can serve as input features to supervised learning, used to build discriminative markers, and directly used as functional modules. The constructed features are typically compressed representation of input data in a lower dimension. They maintain essential information in the input but are better organized than the input with less noise or artifacts. Therefore, it is easier to build classifiers on the summarized features than raw input data, and the success of a classifier heavily depends on the choice of data representation We proved our finding using machine learning classification framework. With our representation, we could enhance simple linear SVM accuracy from 63% to 75%
We also proposed a novel machine learning approach to evaluating the circadian disruption using robust regression as a contextual anomaly detection method. The main aspect of novelty in this work is coming from applying a point anomaly detection technique with respect to a circadian rhythmicity context. To the best of our knowledge, this work is the first which introduced the use of NR1D1/NR1D2 clock genes as prior knowledge to detect genes pathways involved in response to sleep disruption. In the Circadian Disruption Detection (CDD) model, we implemented and validated a model that successfully model the normal samples. While in anomalies samples i.e. samples with significant transcription effect under the circadian disruption, the model was acting poorly. Results of the analysis of variance (ANOVA) and t-test show the benefits of using our robust multi-regression errors as a biological biomarker to detect sleep deprivation using genes microarray data. we found that there was a significant difference between the error distribution for the normal sleep and the anomalies samples at the p