After graduating from my first degree in Molecular Biology and Genetics at University of East Anglia in 2001, I 'converted' to 'dry' science by completing an MSc in Bioinformatics at University of East Anglia, where I started to look into predicting protein disorder from amino acid sequences (2001-2002). I consolidated this conversion by studying for my PhD in Bioinformatics at Manchester University from 2002-2005 (PhD awarded 2007). My PhD focused upon the prediction of transcriptional units by integrating genomic and transcriptomic data. Directly following my PhD, from 2005, I worked as a Research Associate in Bioinformatics at the University of Surrey, where I was involved in the storage and analysis of the high-throughput data generated by the Streptomyces coelicolor International research consortium ActinoGEN. In 2009 I became an academic at the University of Surrey, appointed to Senior Lecturer in 2016.
My research focuses on exploiting data for furthering understanding of biological systems. My research programmes can be broadly classified into; 1) deployment of computational approaches for the analysis, interpretation and exploitation of large-scale biologically derived data, and 2) the development of computational tools and algorithms for the analysis of biological data.
I have led the bioinformatics component of interdisciplinary projects that have thus far attracted >£4.5M and produced more than 29 published, peer-reviewed outputs, the majority of which are recognised as being in top quartile journals.
I have acted as a panel member of the BBSRC BBR panel in 2017 and 2018, and as a 'roving' machine learning expert panel member in BBSRC responsive mode research committee meetings (2017). I have assessed interdisciplinary research proposals for; BBSRC, MRC, Wellcome Trust, Royal Society and the Irish research council.
I am a review editor for the journal Frontiers in Genetics (Bioinformatics and Computational Biology section), and have acted as a reviewer for the journals Nucleic Acids Research, Bioinformatics, BMC Bioinformatics, Journal of the Royal Society Interface, Future Microbiology, Frontiers journals, and F1000 Research.
I have acted as a member of the organising committee for Translation UK 2016, and Technical co-chair of 2012 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology.
My current funded projects include:
£94k MRC iCASE Studentship. 'Hospital sink microbiomes and their contribution to the spread of antimicrobial resistance'. J Ritchie (PI), E Laing, G Moore (PHE).
£482k Alborada Trust. 'Well foal project', assessing microbiota influences on foal health and performance. C Proudman (PI), R La Ragione, E Laing, R Ellis (APHA), F Steinbach (APHA).
£16k UK Space Agency. 'Validation of blood transcriptome-based biomarkers for the effects of microgravity on human physiology'. S Archer (PI), D Dijk, E Laing, C Moller-Levet
£94k Pirbright Institute/BBSRC PhD Studentship in collaboration with Merial Animal Health. ‘Using a ‘Vaccinomics’ approach to investigate foot-and-mouth disease virus (FMDV) vaccine quality and characterise immune escape mechanisms’. D King (PI, Pirbright), G Freimanis (Pirbright), E Laing (Surrey).
£454k BBSRC-European Space Agency (AO-13-BR). ‘The effects of bedrest on the circadian organisation of the human blood transcriptome as a model for temporal dysregulation during long-term spaceflight and ageing’. S Archer (PI), D Dijk, E Laing, CP Smith, N Santhi.
£94k BBSRC iCASE PhD Studentship (BB/K01160X/1). The development of a microbial community for increasing wheat crop yield’. Laing E (PI), Avignone-Rossa C, Hodgson S (Symbio Ltd).
My teaching activities are interdisciplinary in nature; teaching computational approaches to those with a biological/health background, and biological principles to those with a computational/theoretical background.
I have created new innovative, interdisciplinary teaching programmes and courses to close the recognised skills gap in computational approaches and quantitative analyses in the life and health sciences, for which I have gained the support of BBSRC and industry.
I currently teach at all HE levels in relation to; bioinformatic approaches, statistics, molecular biology and genetics, and systems biology.
Based on requests, I have run ad hoc workshops related to statistical analysis and computational programming for external institutions and research groups.
I have acted as a reviewer for the textbooks "Introduction to Genomics", by Lesk, Oxford University Press" and "Systems biology in Environmental Research, From the Genome to Epigenome", by Fry, Elsevier.
My current PhD projects include:
David King (Co-supervisor, collaboration with Don King and Graham Freimanis, Pirbright Institute and colleagues in Merial): Using a ‘Vaccinomics’ approach to investigate foot-and-mouth disease virus (FMDV) vaccine quality and characterise immune escape mechanisms
Indre Navickaite (Principal superivosr, collaboration with Claudio Avignone-Rossa and colleagues in Symbio Ltd): The development of a microbial community to improve wheat crop yield
Nadia Mohammed (Co-supervisor, collaboration with Jenny Ritchie and Ginny Moore (PHE)): Hospital sink microbiomes and their contribution to the spread of antimicrobial resistance
Nouf Algnami (Co-supervisor, collaboration with Lillian Tang): Deep Learning to exploit human transcriptomic data
BACKGROUND: Twenty-four-hour rhythmicity in mammalian tissues and organs is driven by local circadian oscillators, systemic factors, the central circadian pacemaker, and light-dark cycles. At the physiological level, the neural and endocrine systems synchronize gene expression in peripheral tissues and organs to the twenty-four-hour day cycle, and disruption of such regulation has been shown to lead to pathological conditions. Thus, monitoring rhythmicity in tissues/organs holds promise for circadian medicine, however most tissues and organs are not easily accessible in humans and alternative approaches to quantify circadian rhythmicity are needed. We investigated the overlap between rhythmic transcripts in human blood and transcripts shown to be rhythmic in 64 tissues/organs of the baboon, how these rhythms are aligned with light-dark cycles and each other, and whether timing of tissue-specific rhythmicity can be predicted from a blood sample. RESULTS: We compared rhythmicity in transcriptomic time series collected from humans and baboons using set logic, circular cross-correlation, circular clustering, functional enrichment analyses and least squares regression. Of the 759 orthologous genes that were rhythmic in human blood, 652 (86%) were also rhythmic in at least one baboon tissue and most of these genes were associated with basic processes such as transcription and protein homeostasis. 109 (17%) of the 652 overlapping rhythmic genes were reported as rhythmic in only one baboon tissue or organ and several of these genes have tissue/organ-specific functions. The timing of human and baboon rhythmic transcripts displayed prominent ‘night’ and ‘day’ clusters, with genes in the dark cluster associated with translation. Alignment between baboon rhythmic transcriptomes and the overlapping human blood transcriptome was significantly closer when light onset, rather than midpoint of light, or end of light period, was used as phase reference point. The timing of overlapping human and baboon rhythmic transcriptomes was significantly correlated in 25 tissue/organs with an average earlier timing of 3.21 h (SD 2.47 h) in human blood. CONCLUSIONS: The human blood transcriptome contains sets of rhythmic genes that overlap with rhythmic genes of tissues/organs in baboon. The rhythmic sets vary across tissues/organs, but the timing of most rhythmic genes is similar in human blood and baboon tissues/organs. These results have implications for development of blood transcriptome-based biomarkers for circadian rhythmicity in tissues and organs.
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 insufficient (< 6 h) or sufficient sleep (~8.6 h) to identify panels of mRNA biomarkers of sleep debt 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.
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.
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.
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. coelicolor.
"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 ...
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.
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) θ power during wakefulness and δ 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 δ 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.
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.
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.
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.
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.
Whilst being closely related to the model actinomycete Streptomyces coelicolor A3(2), S. lividans 66 differs from it in several significant and phenotypically observable ways, including antibiotic production. Previous comparative gene hybridization studies investigating such differences have used low-density (one probe per gene) PCR-based spotted arrays. Here we use new experimentally optimised 104,000 × 60-mer probe arrays to characterize in detail the genomic differences between wild-type S. lividans 66, a derivative industrial strain, TK24, and S. coelicolor M145.
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.
Polymorphisms in the human circadian clock gene PERIOD3 (PER3) are associated with a wide variety of phenotypes such as diurnal preference, delayed sleep phase disorder, sleep homeostasis, cognitive performance, bipolar disorder, type 2 diabetes, cardiac regulation, cancer, light sensitivity, hormone and cytokine secretion, and addiction. However, the molecular mechanisms underlying these phenotypic associations remain unknown. Per3 knockout mice (Per3
Background: DNA microarrays are a key resource for global analysis of genome content, gene expression and the distribution of transcription factor binding sites. We describe the development and application of versatile high density ink-jet in situ-synthesized DNA arrays for the G+C rich bacterium Streptomyces coelicolor. High G+C content DNA probes often perform poorly on arrays, yielding either weak hybridization or non-specific signals. Thus, more than one million 60-mer oligonucleotide probes were experimentally tested for sensitivity and specificity to enable selection of optimal probe sets for the genome microarrays. The heat-shock HspR regulatory system of S. coelicolor, a well-characterized repressor with a small number of known targets, was exploited to test and validate the arrays for use in global chromatin immunoprecipitation-on-chip (ChIP-chip) and gene expression analysis. Results: In addition to confirming dnaK, clpB and lon as in vivo targets of HspR, it was revealed, using a novel ChIPchip data clustering method, that HspR also apparently interacts with ribosomal RNA (rrnD operon) and specific transfer RNA genes (the tRNAGln/tRNAGlu cluster). It is suggested that enhanced synthesis of Glu-tRNAGlu may reflect increased demand for tetrapyrrole biosynthesis following heat-shock. Moreover, it was found that heatshock- induced genes are significantly enriched for Gln/Glu codons relative to the whole genome, a finding that would be consistent with HspR-mediated control of the tRNA species. Conclusions: This study suggests that HspR fulfils a broader, unprecedented role in adaptation to stresses than previously recognized - influencing expression of key components of the translational apparatus in addition to molecular chaperone and protease-encoding genes. It is envisaged that these experimentally optimized arrays will provide a key resource for systems level studies of Streptomyces biology.
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.
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'.
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.
The atypical two-component system (TCS) AbrC1/2/3 (encoded respectively by SCO4598/4597/4596), 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 ACT and RED production and delays morphological development. In contrast, the over-expression of abrC3 in the parent strain leads to a 33% increase in ACT production in liquid medium. Transcriptomic and ChIP-chip analyses of ΔabrC3 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, either to the redZ or to the redD promoters regions. 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 ten-base consensus binding sequence and may be responsible for some of the phenotypes of the ΔabrC3 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 hyper-producer host strains through genetic manipulation of such systems.
Post-transcriptional control of gene expression is mediated via RNA-binding proteins (RBPs) that interact with mRNAs in a combinatorial fashion. While recent global RNA interactome capture experiments expanded the repertoire of cellular RBPs quiet dramatically, little is known about the assembly of RBPs on particular mRNAs; and how these associations change and control the fate of the mRNA in drug-treatment conditions. Here we introduce a novel biochemical approach, termed tobramycinbased tandem RNA isolation procedure (tobTRIP), to quantify proteins associated with the 3'UTRs of cyclin-dependent kinase inhibitor 1B (CDKN1B/p27Kip1) mRNAs in vivo. P27Kip1 plays an important role in mediating a cell's response to cisplatin (CP), a widely used chemotherapeutic cancer drug that induces DNA damage and cell cycle arrest. We found that p27Kip1 mRNA is stabilized upon CP treatment of HEK293 cells through elements in its 3'UTR. Applying tobTRIP, we further compared the associated proteins in CP and non-treated cells, and identified more than fifty interacting RBPs, many functionally related and evoking a coordinated response. Knock-downs of several of the identified RBPs in HEK293 cells confirmed their involvement in CP-induced p27 mRNA regulation; while knock-down of the KH-type splicing regulatory protein (KHSRP) further enhanced the sensitivity of MCF7 adenocarcinoma cancer cells to CP treatment. Our results highlight the benefit of specific in vivo mRNA-protein interactome capture to reveal post-transcriptional regulatory networks implicated in cellular drug response and adaptation.
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.
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.
Background: In Streptomyces coelicolor, bldA encodes the only tRNA for a rare leucine codon, UUA. This tRNA is unnecessary for growth, but is required for some aspects of secondary metabolism and morphological development. We describe a transcriptomic and proteomic analysis of the effects of deleting bldA on cellular processes during submerged culture: conditions relevant to the industrial production of antibiotics. Results: At the end of rapid growth, a co-ordinated transient up-regulation of about 100 genes, including many for ribosomal proteins, was seen in the parent strain but not the ΔbldA mutant. Increased basal levels of the signal molecule ppGpp in the mutant strain may be responsible for this difference. Transcripts or proteins from a further 147 genes classified as bldA-influenced were mostly expressed late in culture in the wild-type, though others were significantly transcribed during exponential growth. Some were involved in the biosynthesis of seven secondary metabolites; and some have probable roles in reorganising metabolism after rapid growth. Many of the 147 genes were "function unknown", and may represent unknown aspects of Streptomyces biology. Only two of the 147 genes contain a TTA codon, but some effects of bldA could be traced to TTA codons in regulatory genes or polycistronic operons. Several proteins were affected posttranslationally by the bldA deletion. There was a statistically significant but weak positive global correlation between transcript and corresponding protein levels. Different technical limitations of the two approaches were a major cause of discrepancies in the results obtained with them. Conclusion: Although deletion of bldA has very conspicuous effects on the gross phenotype, the bldA molecular phenotype revealed by the "dualomic" approach has shown that only about 2% of the genome is affected; but this includes many previously unknown effects at a variety of different levels, including post translational changes in proteins and global cellular physiology.
RNA-binding proteins (RBPs) are key post-transcriptional regulators that play a substantial role during stress adaptation. Recent proteome-wide surveys have uncovered a large number of new and “unconventional” RBPs such as metabolic enzymes, yet little is known about the reconfiguration of the RNA-binding proteome (RBPome) and RNA-enzyme interactions in response to cellular stress. Here, we applied RNA-interactome capture to monitor the dynamics of the mRBPome upon mild oxidative stress in the yeast Saccharomyces cerevisiae. Among the 257 proteins that significantly changed RNA associations, we observed the coordinated remodeling of RNA-binding enzymes — particularly of the central carbon metabolism — that complemented known metabolic responses. Furthermore, we recognized the propensity for paralogous specific alterations of enzyme-RNA interactions. Our results suggest coordinated cross talk between RNA-enzyme interactions and intermediary metabolism to maintain the physiological and molecular balance upon oxidative stress, perhaps through specialization of paralogous during evolution.
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.