Thermodynamic Concepts in the Study of Microbial Populations: Age Structure in Plasmodium falciparum Infected Red Blood Cells

Written by on October 31, 2011 – 9:00 pm -

by Jordi Ferrer, Clara Prats, Daniel López, Jaume Vidal-Mas, Domingo Gargallo-Viola, Antonio Guglietta, Antoni Giró

Variability is a hallmark of microbial systems. On the one hand, microbes are subject to environmental heterogeneity and undergo changeable conditions in their immediate surroundings. On the other hand, microbial populations exhibit high cellular diversity. The relation between microbial diversity and variability of population dynamics is difficult to assess. This connection can be quantitatively studied from a perspective that combines in silico models and thermodynamic methods and interpretations. The infection process of Plasmodium falciparum parasitizing human red blood cells under laboratory cultivation conditions is used to illustrate the potential of Individual-based models in the context of predictive microbiology and parasitology. Experimental data from several in vitro cultures are compared to the outcome of an individual-based model and analysed from a thermodynamic perspective. This approach allows distinguishing between intrinsic and external constraints that give rise to the diversity in the infection forms, and it provides a criterion to quantitatively define transient and stationary regimes in the culture. Increasing the ability of models to discriminate between different states of microbial populations enhances their predictive capability which finally leads to a better the control over culture systems. The strategy here presented is of general application and it can substantially improve modelling of other types of microbial communities.

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Structural Annotation of Mycobacterium tuberculosis Proteome

Written by on October 31, 2011 – 9:00 pm -

by Praveen Anand, Sandhya Sankaran, Sumanta Mukherjee, Kalidas Yeturu, Roman Laskowski, Anshu Bhardwaj, Raghu Bhagavat, OSDD Consortium, Samir K. Brahmachari, Nagasuma Chandra

Of the ∼4000 ORFs identified through the genome sequence of Mycobacterium tuberculosis (TB) H37Rv, experimentally determined structures are available for 312. Since knowledge of protein structures is essential to obtain a high-resolution understanding of the underlying biology, we seek to obtain a structural annotation for the genome, using computational methods. Structural models were obtained and validated for ∼2877 ORFs, covering ∼70% of the genome. Functional annotation of each protein was based on fold-based functional assignments and a novel binding site based ligand association. New algorithms for binding site detection and genome scale binding site comparison at the structural level, recently reported from the laboratory, were utilized. Besides these, the annotation covers detection of various sequence and sub-structural motifs and quaternary structure predictions based on the corresponding templates. The study provides an opportunity to obtain a global perspective of the fold distribution in the genome. The annotation indicates that cellular metabolism can be achieved with only 219 folds. New insights about the folds that predominate in the genome, as well as the fold-combinations that make up multi-domain proteins are also obtained. 1728 binding pockets have been associated with ligands through binding site identification and sub-structure similarity analyses. The resource (http://proline.physics.iisc.ernet.in/Tbstructuralannotation), being one of the first to be based on structure-derived functional annotations at a genome scale, is expected to be useful for better understanding of TB and for application in drug discovery. The reported annotation pipeline is fairly generic and can be applied to other genomes as well.

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Hands-On Parameter Search for Neural Simulations by a MIDI-Controller

Written by on October 31, 2011 – 9:00 pm -

by Hubert Eichner, Alexander Borst

Computational neuroscientists frequently encounter the challenge of parameter fitting – exploring a usually high dimensional variable space to find a parameter set that reproduces an experimental data set. One common approach is using automated search algorithms such as gradient descent or genetic algorithms. However, these approaches suffer several shortcomings related to their lack of understanding the underlying question, such as defining a suitable error function or getting stuck in local minima. Another widespread approach is manual parameter fitting using a keyboard or a mouse, evaluating different parameter sets following the users intuition. However, this process is often cumbersome and time-intensive. Here, we present a new method for manual parameter fitting. A MIDI controller provides input to the simulation software, where model parameters are then tuned according to the knob and slider positions on the device. The model is immediately updated on every parameter change, continuously plotting the latest results. Given reasonably short simulation times of less than one second, we find this method to be highly efficient in quickly determining good parameter sets. Our approach bears a close resemblance to tuning the sound of an analog synthesizer, giving the user a very good intuition of the problem at hand, such as immediate feedback if and how results are affected by specific parameter changes. In addition to be used in research, our approach should be an ideal teaching tool, allowing students to interactively explore complex models such as Hodgkin-Huxley or dynamical systems.

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A Point Mutation in Translation Initiation Factor eIF2B Leads to Function- and Time-Specific Changes in Brain Gene Expression

Written by on October 31, 2011 – 9:00 pm -

by Liraz Marom, Igor Ulitsky, Yuval Cabilly, Ron Shamir, Orna Elroy-Stein

Background

Mutations in eukaryotic translation initiation factor 2B (eIF2B) cause Childhood Ataxia with CNS Hypomyelination (CACH), also known as Vanishing White Matter disease (VWM), which is associated with a clinical pathology of brain myelin loss upon physiological stress. eIF2B is the guanine nucleotide exchange factor (GEF) of eIF2, which delivers the initiator tRNAMet to the ribosome. We recently reported that a R132H mutation in the catalytic subunit of this GEF, causing a 20% reduction in its activity, leads under normal conditions to delayed brain development in a mouse model for CACH/VWM. To further explore the effect of the mutation on global gene expression in the brain, we conducted a wide-scale transcriptome analysis of the first three critical postnatal weeks.

Methodology/Principal Findings

Genome-wide mRNA expression of wild-type and mutant mice was profiled at postnatal (P) days 1, 18 and 21 to reflect the early proliferative stage prior to white matter establishment (P1) and the peak of oligodendrocye differentiation and myelin synthesis (P18 and P21). At each developmental stage, between 441 and 818 genes were differentially expressed in the mutant brain with minimal overlap, generating unique time point-specific gene expression signatures.

Conclusions

The current study demonstrates that a point mutation in eIF2B, a key translation initiation factor, has a massive effect on global gene expression in the brain. The overall changes in expression patterns reflect multiple layers of indirect effects that accumulate as the brain develops and matures. The differentially expressed genes seem to reflect delayed waves of gene expression as well as an adaptation process to cope with hypersensitivity to cellular stress.


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A Multi-Sample Based Method for Identifying Common CNVs in Normal Human Genomic Structure Using High-Resolution aCGH Data

Written by on October 31, 2011 – 9:00 pm -

by Chihyun Park, Jaegyoon Ahn, Youngmi Yoon, Sanghyun Park

Background

It is difficult to identify copy number variations (CNV) in normal human genomic data due to noise and non-linear relationships between different genomic regions and signal intensity. A high-resolution array comparative genomic hybridization (aCGH) containing 42 million probes, which is very large compared to previous arrays, was recently published. Most existing CNV detection algorithms do not work well because of noise associated with the large amount of input data and because most of the current methods were not designed to analyze normal human samples. Normal human genome analysis often requires a joint approach across multiple samples. However, the majority of existing methods can only identify CNVs from a single sample.

Methodology and Principal Findings

We developed a multi-sample-based genomic variations detector (MGVD) that uses segmentation to identify common breakpoints across multiple samples and a k-means-based clustering strategy. Unlike previous methods, MGVD simultaneously considers multiple samples with different genomic intensities and identifies CNVs and CNV zones (CNVZs); CNVZ is a more precise measure of the location of a genomic variant than the CNV region (CNVR).

Conclusions and Significance

We designed a specialized algorithm to detect common CNVs from extremely high-resolution multi-sample aCGH data. MGVD showed high sensitivity and a low false discovery rate for a simulated data set, and outperformed most current methods when real, high-resolution HapMap datasets were analyzed. MGVD also had the fastest runtime compared to the other algorithms evaluated when actual, high-resolution aCGH data were analyzed. The CNVZs identified by MGVD can be used in association studies for revealing relationships between phenotypes and genomic aberrations. Our algorithm was developed with standard C++ and is available in Linux and MS Windows format in the STL library. It is freely available at: http://embio.yonsei.ac.kr/~Park/mgvd.php.


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Pathobiological Implications of MUC16 Expression in Pancreatic Cancer

Written by on October 31, 2011 – 9:00 pm -

by Dhanya Haridas, Subhankar Chakraborty, Moorthy P. Ponnusamy, Imayavaramban Lakshmanan, Satyanarayana Rachagani, Eric Cruz, Sushil Kumar, Srustidhar Das, Subodh M. Lele, Judy M. Anderson, Uwe A. Wittel, Michael A. Hollingsworth, Surinder K. Batra

MUC16 (CA125) belongs to a family of high-molecular weight O-glycosylated proteins known as mucins. While MUC16 is well known as a biomarker in ovarian cancer, its expression pattern in pancreatic cancer (PC), the fourth leading cause of cancer related deaths in the United States, remains unknown. The aim of our study was to analyze the expression of MUC16 during the initiation, progression and metastasis of PC for possible implication in PC diagnosis, prognosis and therapy. In this study, a microarray containing tissues from healthy and PC patients was used to investigate the differential protein expression of MUC16 in PC. MUC16 mRNA levels were also measured by RT-PCR in the normal human pancreatic, pancreatitis, and PC tissues. To investigate its expression pattern during PC metastasis, tissue samples from the primary pancreatic tumor and metastases (from the same patient) in the lymph nodes, liver, lung and omentum from Stage IV PC patients were analyzed. To determine its association in the initiation of PC, tissues from PC patients containing pre-neoplastic lesions of varying grades were stained for MUC16. Finally, MUC16 expression was analyzed in 18 human PC cell lines. MUC16 is not expressed in the normal pancreatic ducts and is strongly upregulated in PC and detected in pancreatitis tissue. It is first detected in the high-grade pre-neoplastic lesions preceding invasive adenocarcinoma, suggesting that its upregulation is a late event during the initiation of this disease. MUC16 expression appears to be stronger in metastatic lesions when compared to the primary tumor, suggesting a role in PC metastasis. We have also identified PC cell lines that express MUC16, which can be used in future studies to elucidate its functional role in PC. Altogether, our results reveal that MUC16 expression is significantly increased in PC and could play a potential role in the progression of this disease.

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Effects of Dietary Fish Oil on the Depletion of Carcinogenic PAH-DNA Adduct Levels in the Liver of B6C3F1 Mouse

Written by on October 31, 2011 – 9:00 pm -

by Guo-Dong Zhou, Huiping Zhu, Tracie D. Phillips, Jianbo Wang, Shi-Zhou Wang, Fen Wang, Brad A. Amendt, Xanthi I. Couroucli, Kirby C. Donnelly, Bhagavatula Moorthy

Many carcinogenic polycyclic aromatic hydrocarbons (PAHs) and their metabolites can bind covalently to DNA. Carcinogen-DNA adducts may lead to mutations in critical genes, eventually leading to cancer. In this study we report that fish oil (FO) blocks the formation of DNA adducts by detoxification of PAHs. B6C3F1 male mice were fed a FO or corn oil (CO) diet for 30 days. The animals were then treated with seven carcinogenic PAHs including benzo(a)pyrene (BaP) with one of two doses via a single intraperitoneal injection. Animals were terminated at 1, 3, or 7 d after treatment. The levels of DNA adducts were analyzed by the 32P-postlabeling assay. Our results showed that the levels of total hepatic DNA adducts were significantly decreased in FO groups compared to CO groups with an exception of low PAH dose at 3 d (P = 0.067). Total adduct levels in the high dose PAH groups were 41.36±6.48 (Mean±SEM) and 78.72±8.03 in 109 nucleotides (P = 0.011), respectively, for the FO and CO groups at 7 d. Animals treated with the low dose (2.5 fold lower) PAHs displayed similar trends. Total adduct levels were 12.21±2.33 in the FO group and 24.07±1.99 in the CO group, P = 0.008. BPDE-dG adduct values at 7 d after treatment of high dose PAHs were 32.34±1.94 (CO group) and 21.82±3.37 (FO group) in 109 nucleotides with P value being 0.035. Low dose groups showed similar trends for BPDE-dG adduct in the two diet groups. FO significantly enhanced gene expression of Cyp1a1 in both the high and low dose PAH groups. Gstt1 at low dose of PAHs showed high levels in FO compared to CO groups with P values being 0.014. Histological observations indicated that FO played a hepatoprotective role during the early stages. Our results suggest that FO has a potential to be developed as a cancer chemopreventive agent.

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Novel Candidate Genes Associated with Hippocampal Oscillations

Written by on October 31, 2011 – 9:00 pm -

by Rick Jansen, Jaap Timmerman, Maarten Loos, Sabine Spijker, Arjen van Ooyen, Arjen B. Brussaard, Huibert D. Mansvelder, The Neuro-Bsik Mouse Phenomics Consortium, August B. Smit, Mathisca de Gunst, Klaus Linkenkaer-Hansen

The hippocampus is critical for a wide range of emotional and cognitive behaviors. Here, we performed the first genome-wide search for genes influencing hippocampal oscillations. We measured local field potentials (LFPs) using 64-channel multi-electrode arrays in acute hippocampal slices of 29 BXD recombinant inbred mouse strains. Spontaneous activity and carbachol-induced fast network oscillations were analyzed with spectral and cross-correlation methods and the resulting traits were used for mapping quantitative trait loci (QTLs), i.e., regions on the genome that may influence hippocampal function. Using genome-wide hippocampal gene expression data, we narrowed the QTLs to eight candidate genes, including Plcb1, a phospholipase that is known to influence hippocampal oscillations. We also identified two genes coding for calcium channels, Cacna1b and Cacna1e, which mediate presynaptic transmitter release and have not been shown to regulate hippocampal network activity previously. Furthermore, we showed that the amplitude of the hippocampal oscillations is genetically correlated with hippocampal volume and several measures of novel environment exploration.

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Long Timescale fMRI Neuronal Adaptation Effects in Human Amblyopic Cortex

Written by on October 31, 2011 – 9:00 pm -

by Xingfeng Li, Damien Coyle, Liam Maguire, Thomas M. McGinnity, Robert F. Hess

An investigation of long timescale (5 minutes) fMRI neuronal adaptation effects, based on retinotopic mapping and spatial frequency stimuli, is presented in this paper. A hierarchical linear model was developed to quantify the adaptation effects in the visual cortex. The analysis of data involved studying the retinotopic mapping and spatial frequency adaptation effects in the amblyopic cortex. Our results suggest that, firstly, there are many cortical regions, including V1, where neuronal adaptation effects are reduced in the cortex in response to amblyopic eye stimulation. Secondly, our results show the regional contribution is different, and it seems to start from V1 and spread to the extracortex regions. Thirdly, our results show that there is greater adaptation to broadband retinotopic mapping as opposed to narrowband spatial frequency stimulation of the amblyopic eye, and we find significant correlation between fMRI response and the magnitude of the adaptation effect, suggesting that the reduced adaptation may be a consequence of the reduced response to different stimuli reported for amblyopic eyes.

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Chronic Fluid Flow Is an Environmental Modifier of Renal Epithelial Function

Written by on October 28, 2011 – 9:00 pm -

by Andrew Resnick

Although solitary or sensory cilia are present in most cells of the body and their existence has been known since the sixties, very little is been known about their functions. One suspected function is fluid flow sensing- physical bending of cilia produces an influx of Ca++, which can then result in a variety of activated signaling pathways. Autosomal Dominant Polycystic Kidney Disease (ADPKD) is a progressive disease, typically appearing in the 5th decade of life and is one of the most common monogenetic inherited human diseases, affecting approximately 600,000 people in the United States. Because ADPKD is a slowly progressing disease, I asked how fluid flow may act, via the primary cilium, to alter epithelial physiology during the course of cell turnover. I performed an experiment to determine under what conditions fluid flow can result in a change of function of renal epithelial tissue. A wildtype epithelial cell line derived the cortical collecting duct of a heterozygous offspring of the Immortomouse (Charles River Laboratory) was selected as our model system. Gentle orbital shaking was used to induce physiologically relevant fluid flow, and periodic measurements of the transepithelial Sodium current were performed. At the conclusion of the experiment, mechanosensitive proteins of interest were visualized by immunostaining. I found that fluid flow, in itself, modifies the transepithelial sodium current, cell proliferation, and the actin cytoskeleton. These results significantly impact the understanding of both the mechanosensation function of primary cilia as well as the understanding of ADPKD disease progression.

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Deep Sequencing the Transcriptome Reveals Seasonal Adaptive Mechanisms in a Hibernating Mammal

Written by on October 28, 2011 – 9:00 pm -

by Marshall Hampton, Richard G. Melvin, Anne H. Kendall, Brian R. Kirkpatrick, Nichole Peterson, Matthew T. Andrews

Mammalian hibernation is a complex phenotype involving metabolic rate reduction, bradycardia, profound hypothermia, and a reliance on stored fat that allows the animal to survive for months without food in a state of suspended animation. To determine the genes responsible for this phenotype in the thirteen-lined ground squirrel (Ictidomys tridecemlineatus) we used the Roche 454 platform to sequence mRNA isolated at six points throughout the year from three key tissues: heart, skeletal muscle, and white adipose tissue (WAT). Deep sequencing generated approximately 3.7 million cDNA reads from 18 samples (6 time points ×3 tissues) with a mean read length of 335 bases. Of these, 3,125,337 reads were assembled into 140,703 contigs. Approximately 90% of all sequences were matched to proteins in the human UniProt database. The total number of distinct human proteins matched by ground squirrel transcripts was 13,637 for heart, 12,496 for skeletal muscle, and 14,351 for WAT. Extensive mitochondrial RNA sequences enabled a novel approach of using the transcriptome to construct the complete mitochondrial genome for I. tridecemlineatus. Seasonal and activity-specific changes in mRNA levels that met our stringent false discovery rate cutoff (1.0×10−11) were used to identify patterns of gene expression involving various aspects of the hibernation phenotype. Among these patterns are differentially expressed genes encoding heart proteins AT1A1, NAC1 and RYR2 controlling ion transport required for contraction and relaxation at low body temperatures. Abundant RNAs in skeletal muscle coding ubiquitin pathway proteins ASB2, UBC and DDB1 peak in October, suggesting an increase in muscle proteolysis. Finally, genes in WAT that encode proteins involved in lipogenesis (ACOD, FABP4) are highly expressed in August, but gradually decline in expression during the seasonal transition to lipolysis.

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Quantitative Bias in Illumina TruSeq and a Novel Post Amplification Barcoding Strategy for Multiplexed DNA and Small RNA Deep Sequencing

Written by on October 28, 2011 – 9:00 pm -

by Filip Van Nieuwerburgh, Sandra Soetaert, Katie Podshivalova, Eileen Ay-Lin Wang, Lana Schaffer, Dieter Deforce, Daniel R. Salomon, Steven R. Head, Phillip Ordoukhanian

Here we demonstrate a method for unbiased multiplexed deep sequencing of RNA and DNA libraries using a novel, efficient and adaptable barcoding strategy called Post Amplification Ligation-Mediated (PALM). PALM barcoding is performed as the very last step of library preparation, eliminating a potential barcode-induced bias and allowing the flexibility to synthesize as many barcodes as needed. We sequenced PALM barcoded micro RNA (miRNA) and DNA reference samples and evaluated the quantitative barcode-induced bias in comparison to the same reference samples prepared using the Illumina TruSeq barcoding strategy. The Illumina TruSeq small RNA strategy introduces the barcode during the PCR step using differentially barcoded primers, while the TruSeq DNA strategy introduces the barcode before the PCR step by ligation of differentially barcoded adaptors. Results show virtually no bias between the differentially barcoded miRNA and DNA samples, both for the PALM and the TruSeq sample preparation methods. We also multiplexed miRNA reference samples using a pre-PCR barcode ligation. This barcoding strategy results in significant bias.

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Functional Correlations of Pathogenesis-Driven Gene Expression Signatures in Tuberculosis

Written by on October 28, 2011 – 9:00 pm -

by Jeroen Maertzdorf, Martin Ota, Dirk Repsilber, Hans J. Mollenkopf, January Weiner, Philip C. Hill, Stefan H. E. Kaufmann

Tuberculosis remains a major health threat and its control depends on improved measures of prevention, diagnosis and treatment. Biosignatures can play a significant role in the development of novel intervention measures against TB and blood transcriptional profiling is increasingly exploited for their rational design. Such profiles also reveal fundamental biological mechanisms associated with the pathology of the disease. We have compared whole blood gene expression in TB patients, as well as in healthy infected and uninfected individuals in a cohort in The Gambia, West Africa and validated previously identified signatures showing high similarities of expression profiles among different cohorts. In this study, we applied a unique combination of classical gene expression analysis with pathway and functional association analysis integrated with intra-individual expression correlations. These analyses were employed for identification of new disease-associated gene signatures, identifying a network of Fc gamma receptor 1 signaling with correlating transcriptional activity as hallmark of gene expression in TB. Remarkable similarities to characteristic signatures in the autoimmune disease systemic lupus erythematosus (SLE) were observed. Functional gene clusters of immunoregulatory interactions involving the JAK-STAT pathway; sensing of microbial patterns by Toll-like receptors and IFN-signaling provide detailed insights into the dysregulation of critical immune processes in TB, involving active expression of both pro-inflammatory and immunoregulatory systems. We conclude that transcriptomics (i) provides a robust system for identification and validation of biosignatures for TB and (ii) application of integrated analysis tools yields novel insights into functional networks underlying TB pathogenesis.

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The Interaction between the First Transmembrane Domain and the Thumb of ASIC1a Is Critical for Its N-Glycosylation and Trafficking

Written by on October 28, 2011 – 9:00 pm -

by Lan Jing, Yu-Qing Jiang, Qian Jiang, Bin Wang, Xiang-Ping Chu, Xiang-ming Zha

Acid-sensing ion channel-1a (ASIC1a), the primary proton receptor in the brain, contributes to multiple diseases including stroke, epilepsy and multiple sclerosis. Thus, a better understanding of its biogenesis will provide important insights into the regulation of ASIC1a in diseases. Interestingly, ASIC1a contains a large, yet well organized ectodomain, which suggests the hypothesis that correct formation of domain-domain interactions at the extracellular side is a key regulatory step for ASIC1a maturation and trafficking. We tested this hypothesis here by focusing on the interaction between the first transmembrane domain (TM1) and the thumb of ASIC1a, an interaction known to be critical in channel gating. We mutated Tyr71 and Trp287, two key residues involved in the TM1-thumb interaction in mouse ASIC1a, and found that both Y71G and W287G decreased synaptic targeting and surface expression of ASIC1a. These defects were likely due to altered folding; both mutants showed increased resistance to tryptic cleavage, suggesting a change in conformation. Moreover, both mutants lacked the maturation of N-linked glycans through mid to late Golgi. These data suggest that disrupting the interaction between TM1 and thumb alters ASIC1a folding, impedes its glycosylation and reduces its trafficking. Moreover, reducing the culture temperature, an approach commonly used to facilitate protein folding, increased ASIC1a glycosylation, surface expression, current density and slowed the rate of desensitization. These results suggest that correct folding of extracellular ectodomain plays a critical role in ASIC1a biogenesis and function.

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Lrp Acts as Both a Positive and Negative Regulator for Type 1 Fimbriae Production in Salmonella enterica Serovar Typhimurium

Written by on October 28, 2011 – 9:00 pm -

by Chang-Ho Baek, Ho-Young Kang, Kenneth L. Roland, Roy Curtiss

Leucine-responsive regulatory protein (Lrp) is known to be an indirect activator of type 1 fimbriae synthesis in Salmonella enterica serovar Typhimurium via direct regulation of FimZ, a direct positive regulator for type 1 fimbriae production. Using RT-PCR, we have shown previously that fimA transcription is dramatically impaired in both lrp-deletion (Δlrp) and constitutive-lrp expression (lrpC) mutant strains. In this work, we used chromosomal PfimA-lacZ fusions and yeast agglutination assays to confirm and extend our previous results. Direct binding of Lrp to PfimA was shown by an electrophoretic mobility shift assay (EMSA) and DNA footprinting assay. Site-directed mutagenesis revealed that the Lrp-binding motifs in PfimA play a role in both activation and repression of type 1 fimbriae production. Overproduction of Lrp also abrogates fimZ expression. EMSA data showed that Lrp and FimZ proteins independently bind to PfimA without competitive exclusion. In addition, both Lrp and FimZ binding to PfimA caused a hyper retardation (supershift) of the DNA-protein complex compared to the shift when each protein was present alone. Nutrition-dependent cellular Lrp levels closely correlated with the amount of type 1 fimbriae production. These observations suggest that Lrp plays important roles in type 1 fimbriation by acting as both a positive and negative regulator and its effect depends, at least in part, on the cellular concentration of Lrp in response to the nutritional environment.

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