Participation of Insulin-Like Growth Factor 1 in Articular Cartilage Remodeling

Upon cartilage damage its natural recovery takes a long time. This is due to several reasons: the absence of blood vessels and low metabolic activity. In this regard, it is relevant to study the mechanism of operation of all components involved in the remodeling of cartilage tissue. For this purpose, protein insulin-like growth factor 1 (IGF-1) was taken as an object of research, since one of its main functions is regulation of cell proliferation, which is closely related to the process of cartilage tissue repair. It is known that in recent years, scientific studies have been conducted on the effect of IGF-1 on the remodeling of cartilage tissues, but in combination with other substances that stimulate more active cell regeneration. This review presents the features of the functional properties and protein structure and its main influence on chondrocyte proliferation for further development of accelerated and effective methods of IGF-1 action on cell growth and repair. The phylogenetic analysis of IGF-1 showed the most related organism for human IGF-1 and structural differences of its protein from human, which are inextricably linked with the functional characteristics of each of the organisms. The results of phylogenetic analysis in the future will identify the object for laboratory research in this question and the search for optimal ways to accelerate the process of remodeling of cartilage joints.

Antibiotic Tolerance: Distinguishing between Classical Resistance and Persistence in a Macrophage Infection Model

Burkholderia pseudomallei is a Gram-negative bacillus and facultative intracellular pathogen. It causes the disease melioidosis, which is a potentially fatal human disease found throughout the world but particularly in Southeast Asia and Northern Australia. B. pseudomallei is inherently antibiotic resistant and therefore new therapies are needed to combat this pathogen. Previous studies with the related organism Burkholderia thailandensis have shown that the antibiotic ceftazidime does not eliminate all bacteria in an in vitro macrophage model, and the remaining bacteria could still pose a health threat to a potential host. Due to their survival in the presence of antibiotics, we hypothesized that the remaining bacteria were one of two types of antibiotic tolerant cells: classically antibiotic resistant cells or persister cells. To test our hypothesis we isolated the bacteria that had survived ceftazidime treatment in the macrophage infection model and performed additional in vitro experiments to show that the surviving bacteria are neither antibiotic resistant nor persister cells. Instead, they are still susceptible to high doses (200 μg/ml) of the antibiotic over a period of 48 hours (p<0.001). We believe the bacteria survive exposure to the antibiotic during the macrophage infection because of their ability to move between intracellular and extracellular compartments, thus avoiding the antibiotic and its deadly effects. Our results provide evidence to suggest that intracellular pathogens, through movement between intracellular and extracellular compartments, may be protected from the effects of antibiotics in similar macrophage infection models.

Draft Genome Sequence of Pseudomonas chlororaphis ATCC 9446, a Nonpathogenic Bacterium with Bioremediation and Industrial Potential

ABSTRACT Pseudomonas chlororaphis strain ATCC 9446 is a biocontrol-related organism. We report here its draft genome sequence assembled into 35 contigs consisting of 6,783,030 bp. Genome annotation predicted a total of 6,200 genes, 6,128 coding sequences, 81 pseudogenes, 58 tRNAs, 4 noncoding RNAs (ncRNAs), and 41 frameshifted genes.

Antibodies against In Vivo-Expressed Antigens Are Sufficient To Protect against Lethal Aerosol Infection with Burkholderia mallei and Burkholderia pseudomallei

ABSTRACT Burkholderia mallei, a facultative intracellular bacterium and tier 1 biothreat, causes the fatal zoonotic disease glanders. The organism possesses multiple genes encoding autotransporter proteins, which represent important virulence factors and targets for developing countermeasures in pathogenic Gram-negative bacteria. In the present study, we investigated one of these autotransporters, BatA, and demonstrate that it displays lipolytic activity, aids in intracellular survival, is expressed in vivo, elicits production of antibodies during infection, and contributes to pathogenicity in a mouse aerosol challenge model. A mutation in the batA gene of wild-type strain ATCC 23344 was found to be particularly attenuating, as BALB/c mice infected with the equivalent of 80 median lethal doses cleared the organism. This finding prompted us to test the hypothesis that vaccination with the batA mutant strain elicits protective immunity against subsequent infection with wild-type bacteria. We discovered that not only does vaccination provide high levels of protection against lethal aerosol challenge with B. mallei ATCC 23344, it also protects against infection with multiple isolates of the closely related organism and causative agent of melioidosis, Burkholderia pseudomallei. Passive-transfer experiments also revealed that the protective immunity afforded by vaccination with the batA mutant strain is predominantly mediated by IgG antibodies binding to antigens expressed exclusively in vivo. Collectively, our data demonstrate that BatA is a target for developing medical countermeasures and that vaccination with a mutant lacking expression of the protein provides a platform to gain insights regarding mechanisms of protective immunity against B. mallei and B. pseudomallei, including antigen discovery.

MetaGenSense: A web-application for analysis and exploration of high throughput sequencing metagenomic data

The detection and characterization of emerging infectious agents has been a continuing public health concern. High Throughput Sequencing (HTS) or Next-Generation Sequencing (NGS) technologies have proven to be promising approaches for efficient and unbiased detection of pathogens in complex biological samples, providing access to comprehensive analyses. As NGS approaches typically yield millions of putatively representative reads per sample, efficient data management and visualization resources have become mandatory. Most usually, those resources are implemented through a dedicated Laboratory Information Management System (LIMS), solely to provide perspective regarding the available information. We developed an easily deployable web-interface, facilitating management and bioinformatics analysis of metagenomics data-samples. It was engineered to run associated and dedicated Galaxy workflows for the detection and eventually classification of pathogens. The web application allows easy interaction with existing Galaxy metagenomic workflows, facilitates the organization, exploration and aggregation of the most relevant sample-specific sequences among millions of genomic sequences, allowing them to determine their relative abundance, and associate them to the most closely related organism or pathogen. The user-friendly Django-Based interface, associates the users’ input data and its metadata through a bio-IT provided set of resources (a Galaxy instance, and both sufficient storage and grid computing power). Galaxy is used to handle and analyze the user’s input data from loading, indexing, mapping, assembly and DB-searches. Interaction between our application and Galaxy is ensured by the BioBlend library, which gives API-based access to Galaxy’s main features. Metadata about samples, runs, as well as the workflow results are stored in the LIMS. For metagenomic classification and exploration purposes, we show, as a proof of concept, that integration of intuitive exploratory tools, like Krona for representation of taxonomic classification, can be achieved very easily. In the trend of Galaxy, the interface enables the sharing of scientific results to fellow team members.

MetaGenSense: A web-application for analysis and exploration of high throughput sequencing metagenomic data

The detection and characterization of emerging infectious agents has been a continuing public health concern. High Throughput Sequencing (HTS) or Next-Generation Sequencing (NGS) technologies have proven to be promising approaches for efficient and unbiased detection of pathogens in complex biological samples, providing access to comprehensive analyses. As NGS approaches typically yield millions of putatively representative reads per sample, efficient data management and visualization resources have become mandatory. Most usually, those resources are implemented through a dedicated Laboratory Information Management System (LIMS), solely to provide perspective regarding the available information. We developed an easily deployable web-interface, facilitating management and bioinformatics analysis of metagenomics data-samples. It was engineered to run associated and dedicated Galaxy workflows for the detection and eventually classification of pathogens. The web application allows easy interaction with existing Galaxy metagenomic workflows, facilitates the organization, exploration and aggregation of the most relevant sample-specific sequences among millions of genomic sequences, allowing them to determine their relative abundance, and associate them to the most closely related organism or pathogen. The user-friendly Django-Based interface, associates the users’ input data and its metadata through a bio-IT provided set of resources (a Galaxy instance, and both sufficient storage and grid computing power). Galaxy is used to handle and analyze the user’s input data from loading, indexing, mapping, assembly and DB-searches. Interaction between our application and Galaxy is ensured by the BioBlend library, which gives API-based access to Galaxy’s main features. Metadata about samples, runs, as well as the workflow results are stored in the LIMS. For metagenomic classification and exploration purposes, we show, as a proof of concept, that integration of intuitive exploratory tools, like Krona for representation of taxonomic classification, can be achieved very easily. In the trend of Galaxy, the interface enables the sharing of scientific results to fellow team members.

Characterization of SlyA in Shigella flexneri Identifies a Novel Role in Virulence

The SlyA transcriptional regulator has important roles in the virulence and pathogenesis of several members of theEnterobacteriaceaefamily, includingSalmonella entericaserovar Typhimurium andEscherichia coli. Despite the identification of theslyAgene inShigella flexnerinearly 2 decades ago, as well as the significant conservation of SlyA among enteric bacteria, the role of SlyA inShigellaremains unknown. The genes regulated by SlyA in closely related organisms often are absent from or mutated inS. flexneri, and consequently many described SlyA-dependent phenotypes are not present. By characterizing the expression ofslyAand determining its ultimate effect in this highly virulent organism, we postulated that novel SlyA-regulated virulence phenotypes would be identified. In this study, we report the first analysis of SlyA inShigellaand show that (i) theslyAgene is transcribed and ultimately translated into protein, (ii)slyApromoter activity is maximal during stationary phase and is negatively autoregulated and positively regulated by the PhoP response regulator, (iii) the exogenous expression ofslyArescues transcription and virulence-associated deficiencies during virulence-repressed conditions, and (iv) the absence ofslyAsignificantly decreases acid resistance, demonstrating a novel and important role inShigellavirulence. Cumulatively, our study illustrates unexpected parallels between the less conservedS. flexneriandS. TyphimuriumslyApromoters as well as a unique role for SlyA inShigellavirulence that has not been described previously in any closely related organism.