Human parvovirus 4 'PARV4' remains elusive despite a decade of study

Human parvovirus 4 ('PARV4') is a small DNA tetraparvovirus, first reported in 2005. In some populations, PARV4 infection is uncommon, and evidence of exposure is found only in individuals with risk factors for parenteral infection who are infected with other blood-borne viruses. In other settings, seroprevalence studies suggest an endemic, age-associated transmission pattern, independent of any specific risk factors. The clinical impact of PARV4 infection remains uncertain, but reported disease associations include an influenza-like syndrome, encephalitis, acceleration of HIV disease, and foetal hydrops. In this review, we set out to report progress updates from the recent literature, focusing on the investigation of cohorts in different geographical settings, now including insights from Asia, the Middle East, and South America, and discussing whether attributes of viral or host populations underpin the striking differences in epidemiology. We review progress in understanding viral phylogeny and biology, approaches to diagnostics, and insights that might be gained from studies of closely related animal pathogens. Crucial questions about pathogenicity remain unanswered, but we highlight new evidence supporting a possible link between PARV4 and an encephalitis syndrome. The unequivocal evidence that PARV4 is endemic in certain populations should drive ongoing research efforts to understand risk factors and routes of transmission and to gain new insights into the impact of this virus on human health

Inferring the conservative causal core of gene regulatory networks

<p>Abstract</p> <p>Background</p> <p>Inferring gene regulatory networks from large-scale expression data is an important problem that received much attention in recent years. These networks have the potential to gain insights into causal molecular interactions of biological processes. Hence, from a methodological point of view, reliable estimation methods based on observational data are needed to approach this problem practically.</p> <p>Results</p> <p>In this paper, we introduce a novel gene regulatory network inference (GRNI) algorithm, called C3NET. We compare C3NET with four well known methods, ARACNE, CLR, MRNET and RN, conducting in-depth numerical ensemble simulations and demonstrate also for biological expression data from <it>E. coli </it>that C3NET performs consistently better than the best known GRNI methods in the literature. In addition, it has also a low computational complexity. Since C3NET is based on estimates of mutual information values in conjunction with a maximization step, our numerical investigations demonstrate that our inference algorithm exploits causal structural information in the data efficiently.</p> <p>Conclusions</p> <p>For systems biology to succeed in the long run, it is of crucial importance to establish methods that extract large-scale gene networks from high-throughput data that reflect the underlying causal interactions among genes or gene products. Our method can contribute to this endeavor by demonstrating that an inference algorithm with a neat design permits not only a more intuitive and possibly biological interpretation of its working mechanism but can also result in superior results.</p

Inferring the conservative causal core of gene regulatory networks

<p>Abstract</p> <p>Background</p> <p>Inferring gene regulatory networks from large-scale expression data is an important problem that received much attention in recent years. These networks have the potential to gain insights into causal molecular interactions of biological processes. Hence, from a methodological point of view, reliable estimation methods based on observational data are needed to approach this problem practically.</p> <p>Results</p> <p>In this paper, we introduce a novel gene regulatory network inference (GRNI) algorithm, called C3NET. We compare C3NET with four well known methods, ARACNE, CLR, MRNET and RN, conducting in-depth numerical ensemble simulations and demonstrate also for biological expression data from <it>E. coli </it>that C3NET performs consistently better than the best known GRNI methods in the literature. In addition, it has also a low computational complexity. Since C3NET is based on estimates of mutual information values in conjunction with a maximization step, our numerical investigations demonstrate that our inference algorithm exploits causal structural information in the data efficiently.</p> <p>Conclusions</p> <p>For systems biology to succeed in the long run, it is of crucial importance to establish methods that extract large-scale gene networks from high-throughput data that reflect the underlying causal interactions among genes or gene products. Our method can contribute to this endeavor by demonstrating that an inference algorithm with a neat design permits not only a more intuitive and possibly biological interpretation of its working mechanism but can also result in superior results.</p

Differential Gene Expression and Adherence of Escherichia coli O157:H7 In Vitro and in Ligated Pig Intestines

BACKGROUND: Escherichia coli O157:H7 strain 86-24 grown in MacConkey broth (MB) shows almost no adherence to cultured epithelial cells but adheres well in pig ligated intestines. This study investigated the mechanisms associated with the difference between in-vitro and in-vivo adherence of the MB culture. METHODOLOGY/PRINCIPAL FINDINGS: It was found that decreased adherence in vitro by bacteria grown in MB was mainly due to lactose, possibly implicating the involvement of carbon catabolite repression (CCR). Expression of selected virulence-related genes associated with adherence and CCR was then examined by quantitative PCR. When bacteria were grown in MB and Brain Heart Infusion with NaHCO(3) (BHIN) plus lactose, pH was reduced to 5.5-5.9 and there was a significant decrease in expression of the locus of enterocyte effacement (LEE) genes eae, tir, espD, grlA/R and ler, and an increase in cya (cAMP), and two negative regulators of the LEE, gadE and hfq. Putative virulence genes stcE, hlyA, ent and nleA were also decreased in vitro. Reversal of these changes was noted for bacteria recovered from the intestine, where transcripts for qseF and fis and putative virulence factors AidA(15), TerC and Ent/EspL2 were significantly increased, and transcripts for AIDA(48), Iha, UreC, Efa1A, Efa1B, ToxB, EhxA, StcE, NleA and NleB were expressed at high levels. CONCLUSIONS/SIGNIFICANCE: Presence of lactose resulted in decreased expression of LEE genes and the failure of EHEC O157:H7 to adhere to epithelial cells in vitro but this repression was overcome in vivo. CCR and/or acidic pH may have played a role in repression of the LEE genes. Bacterial pathogens need to integrate their nutritional metabolism with expression of virulence genes but little is known of how this is done in E. coli O157:H7. This study indicates one aspect of the subject that should be investigated further

Lysogeny with Shiga Toxin 2-Encoding Bacteriophages Represses Type III Secretion in Enterohemorrhagic Escherichia coli

Lytic or lysogenic infections by bacteriophages drive the evolution of enteric bacteria. Enterohemorrhagic Escherichia coli (EHEC) have recently emerged as a significant zoonotic infection of humans with the main serotypes carried by ruminants. Typical EHEC strains are defined by the expression of a type III secretion (T3S) system, the production of Shiga toxins (Stx) and association with specific clinical symptoms. The genes for Stx are present on lambdoid bacteriophages integrated into the E. coli genome. Phage type (PT) 21/28 is the most prevalent strain type linked with human EHEC infections in the United Kingdom and is more likely to be associated with cattle shedding high levels of the organism than PT32 strains. In this study we have demonstrated that the majority (90%) of PT 21/28 strains contain both Stx2 and Stx2c phages, irrespective of source. This is in contrast to PT 32 strains for which only a minority of strains contain both Stx2 and 2c phages (28%). PT21/28 strains had a lower median level of T3S compared to PT32 strains and so the relationship between Stx phage lysogeny and T3S was investigated. Deletion of Stx2 phages from EHEC strains increased the level of T3S whereas lysogeny decreased T3S. This regulation was confirmed in an E. coli K12 background transduced with a marked Stx2 phage followed by measurement of a T3S reporter controlled by induced levels of the LEE-encoded regulator (Ler). The presence of an integrated Stx2 phage was shown to repress Ler induction of LEE1 and this regulation involved the CII phage regulator. This repression could be relieved by ectopic expression of a cognate CI regulator. A model is proposed in which Stx2-encoding bacteriophages regulate T3S to co-ordinate epithelial cell colonisation that is promoted by Stx and secreted effector proteins

Modulation of host cell processes by T3SS effectors

Two of the enteric Escherichia coli pathotypes-enteropathogenic E. coli (EPEC) and enterohaemorrhagic E. coli (EHEC)-have a conserved type 3 secretion system which is essential for virulence. The T3SS is used to translocate between 25 and 50 bacterial proteins directly into the host cytosol where they manipulate a variety of host cell processes to establish a successful infection. In this chapter, we discuss effectors from EPEC/EHEC in the context of the host proteins and processes that they target-the actin cytoskeleton, small guanosine triphosphatases and innate immune signalling pathways that regulate inflammation and cell death. Many of these translocated proteins have been extensively characterised, which has helped obtain insights into the mechanisms of pathogenesis of these bacteria and also understand the host pathways they target in more detail. With increasing knowledge of the positive and negative regulation of host signalling pathways by different effectors, a future challenge is to investigate how the specific effector repertoire of each strain cooperates over the course of an infection

Characterization of the Escherichia coli O157:H7 Sakai GadE Regulon▿ †

Integrating laterally acquired virulence genes into the backbone regulatory network is important for the pathogenesis of Escherichia coli O157:H7, which has captured many virulence genes through horizontal transfer during evolution. GadE is an essential transcriptional activator of the glutamate decarboxylase (GAD) system, the most efficient acid resistance (AR) mechanism in E. coli. The full contribution of GadE to the AR and virulence of E. coli O157:H7 remains largely unknown. We inactivated gadE in E. coli O157:H7 Sakai and compared global transcription profiles of the mutant with that of the wild type in the exponential and stationary phases of growth. Inactivation of gadE significantly altered the expression of 60 genes independently of the growth phase and of 122 genes in a growth phase-dependent manner. Inactivation of gadE markedly downregulated the expression of gadA, gadB, and gadC and of many acid fitness island genes. Nineteen genes encoded on the locus of enterocyte effacement (LEE), including ler, showed a significant increase in expression upon gadE inactivation. Inactivation of ler in the ΔgadE strain reversed the effect of gadE deletion on LEE expression, indicating that Ler is necessary for LEE repression by GadE. GadE is also involved in downregulation of LEE expression under conditions of moderately acidic pH. Characterization of AR of the ΔgadE strain revealed that GadE is indispensable for a functional GAD system and for survival of E. coli O157:H7 in a simulated gastric environment. Altogether, these data indicate that GadE is critical for the AR of E. coli O157:H7 and that it plays an important role in virulence by downregulating expression of LEE