Characterization of Biofilm Formation by Borrelia burgdorferi In Vitro

Borrelia burgdorferi, the causative agent of Lyme disease, has long been known to be capable of forming aggregates and colonies. It was recently demonstrated that Borrelia burgdorferi aggregate formation dramatically changes the in vitro response to hostile environments by this pathogen. In this study, we investigated the hypothesis that these aggregates are indeed biofilms, structures whose resistance to unfavorable conditions are well documented. We studied Borrelia burgdorferi for several known hallmark features of biofilm, including structural rearrangements in the aggregates, variations in development on various substrate matrices and secretion of a protective extracellular polymeric substance (EPS) matrix using several modes of microscopic, cell and molecular biology techniques. The atomic force microscopic results provided evidence that multilevel rearrangements take place at different stages of aggregate development, producing a complex, continuously rearranging structure. Our results also demonstrated that Borrelia burgdorferi is capable of developing aggregates on different abiotic and biotic substrates, and is also capable of forming floating aggregates. Analyzing the extracellular substance of the aggregates for potential exopolysaccharides revealed the existence of both sulfated and non-sulfated/carboxylated substrates, predominately composed of an alginate with calcium and extracellular DNA present. In summary, we have found substantial evidence that Borrelia burgdorferi is capable of forming biofilm in vitro. Biofilm formation by Borrelia species might play an important role in their survival in diverse environmental conditions by providing refuge to individual cells.     

An integrated pathway system modeling of Saccharomyces cerevisiae HOG pathway: a Petri net based approach

Biochemical networks comprise many diverse components and interactions between them. It has intracellular signaling, metabolic and gene regulatory pathways which are highly integrated and whose responses are elicited by extracellular actions. Previous modeling techniques mostly consider each pathway independently without focusing on the interrelation of these which actually functions as a single system. In this paper, we propose an approach of modeling an integrated pathway using an event-driven modeling tool, i.e., Petri nets (PNs). PNs have the ability to simulate the dynamics of the system with high levels of accuracy. The integrated set of signaling, regulatory and metabolic reactions involved in Saccharomyces cerevisiae’s HOG pathway has been collected from the literature. The kinetic parameter values have been used for transition firings. The dynamics of the system has been simulated and the concentrations of major biological species over time have been observed. The phenotypic characteristics of the integrated system have been investigated under two conditions, viz., under the absence and presence of osmotic pressure. The results have been validated favorably with the existing experimental results. We have also compared our study with the study of idFBA (Lee et al., PLoS Comput Biol 4:e1000–e1086, 2008) and pointed out the differences between both studies. We have simulated and monitored concentrations of multiple biological entities over time and also incorporated feedback inhibition by Ptp2 which has not been included in the idFBA study. We have concluded that our study is the first to the best of our knowledge to model signaling, metabolic and regulatory events in an integrated form through PN model framework. This study is useful in computational simulation of system dynamics for integrated pathways as there are growing evidences that the malfunctioning of the interplay among these pathways is associated with disease.     

Design and synthesis of (4E)-4-(4-substitutedbenzylideneamino)-3-substituted-2,3-dihydro-2-thioxothiazole-5-carbonitrile as novel A2A receptor antagonists

Novel 2-thioxothiazole derivatives (6–19) as potential adenosine A_2A receptor (A_2AR) antagonists were synthesized. The strong interaction of the compounds (6–19) with A_2AR in docking study was confirmed by high binding affinity with human A_2AR expressed in HEK293T cells using radioligand-binding assay. The compound 19 demonstrated very high selectivity for A_2AR as compared to standard A_2AR antagonist SCH58261. Decrease in A_2AR-coupled release of endogenous cAMP in treated HEK293T cells demonstrated in vitro A_2AR antagonist potential of the compound 19. Attenuation in haloperidol-induced impairment (catalepsy) in Swiss albino male mice pre-treated with compound 19 is evocative to explore its prospective in therapy of PD.     

Comparing methods for metabolic network analysis and an application to metabolic engineering

Bioinformatics tools have facilitated the reconstruction and analysis of cellular metabolism of various organisms based on information encoded in their genomes. Characterization of cellular metabolism is useful to understand the phenotypic capabilities of these organisms. It has been done quantitatively through the analysis of pathway operations. There are several in silico approaches for analyzing metabolic networks, including structural and stoichiometric analysis, metabolic flux analysis, metabolic control analysis, and several kinetic modeling based analyses. They can serve as a virtual laboratory to give insights into basic principles of cellular functions. This article summarizes the progress and advances in software and algorithm development for metabolic network analysis, along with their applications relevant to cellular physiology, and metabolic engineering with an emphasis on microbial strain optimization. Moreover, it provides a detailed comparative analysis of existing approaches under different categories.     

Quality control and integration of genotypes from two calling pipelines for whole genome sequence data in the Alzheimer's disease sequencing project

The Alzheimer's Disease Sequencing Project (ADSP) performed whole genome sequencing (WGS) of 584 subjects from 111 multiplex families at three sequencing centers. Genotype calling of single nucleotide variants (SNVs) and insertion-deletion variants (indels) was performed centrally using GATK-HaplotypeCaller and Atlas V2. The ADSP Quality Control (QC) Working Group applied QC protocols to project-level variant call format files (VCFs) from each pipeline, and developed and implemented a novel protocol, termed “consensus calling,” to combine genotype calls from both pipelines into a single high-quality set. QC was applied to autosomal bi-allelic SNVs and indels, and included pipeline-recommended QC filters, variant-level QC, and sample-level QC. Low-quality variants or genotypes were excluded, and sample outliers were noted. Quality was assessed by examining Mendelian inconsistencies (MIs) among 67 parent-offspring pairs, and MIs were used to establish additional genotype-specific filters for GATK calls. After QC, 578 subjects remained. Pipeline-specific QC excluded ~12.0% of GATK and 14.5% of Atlas SNVs. Between pipelines, ~91% of SNV genotypes across all QCed variants were concordant; 4.23% and 4.56% of genotypes were exclusive to Atlas or GATK, respectively; the remaining ~0.01% of discordant genotypes were excluded. For indels, variant-level QC excluded ~36.8% of GATK and 35.3% of Atlas indels. Between pipelines, ~55.6% of indel genotypes were concordant; while 10.3% and 28.3% were exclusive to Atlas or GATK, respectively; and ~0.29% of discordant genotypes were. The final WGS consensus dataset contains 27,896,774 SNVs and 3,133,926 indels and is publicly available.     

The Hha–TomB toxin–antitoxin module in Salmonella enterica serovar Typhimurium limits its intracellular survival profile and regulates host immune response

Cell Biology and Toxicology - The key to bacterial virulence relies on an exquisite balance of signals between microbe and hosts. Bacterial toxin–antitoxin (TA) system is known to play a...     

Stress fiber growth and remodeling determines cellular morphomechanics under uniaxial cyclic stretch

Biomechanics and Modeling in Mechanobiology - Stress fibers in the cytoskeleton are essential in maintaining cellular shape and influence cellular adhesion and migration. Cyclic uniaxial stretching...     

Deep,Quantitative Coverage of the Lysine Acetylome Using Novel Anti-acetyl-lysine Antibodies and an Optimized Proteomic Workflow

Introduction of antibodies specific for acetylated lysine has significantly improved the detection of endogenous acetylation sites by mass spectrometry. Here, we describe a new, commercially available mixture of anti-lysine acetylation (Kac) antibodies and show its utility for in-depth profiling of the acetylome. Specifically, seven complementary monoclones with high specificity for Kac were combined into a final anti-Kac reagent which results in at least a twofold increase in identification of Kac peptides over a commonly used Kac antibody. We outline optimal antibody usage conditions, effective offline basic reversed phase separation, and use of state-of-the-art LC-MS technology for achieving unprecedented coverage of the acetylome. The methods were applied to quantify acetylation sites in suberoylanilide hydroxamic acid-treated Jurkat cells. Over 10,000 Kac peptides from over 3000 Kac proteins were quantified from a single stable isotope labeling by amino acids in cell culture labeled sample using 7.5 mg of peptide input per state. This constitutes the deepest coverage of acetylation sites in quantitative experiments obtained to-date. The approach was also applied to breast tumor xenograft samples using isobaric mass tag labeling of peptides (iTRAQ4, TMT6 and TMT10-plex reagents) for quantification. Greater than 6700 Kac peptides from over 2300 Kac proteins were quantified using 1 mg of tumor protein per iTRAQ 4-plex channel. The novel reagents and methods we describe here enable quantitative, global acetylome analyses with depth and sensitivity approaching that obtained for other well-studied post-translational modifications such as phosphorylation and ubiquitylation, and should have widespread application in biological and clinical studies employing mass spectrometry-based proteomics.Lysine acetylation (Kac)¹ is a well conserved, reversible post-translational modification (PTM) involved in multiple cellular processes (1). Acetylation is regulated by two classes of enzymes: lysine acetyltransferases (KATs) and histone deacetylases (HDACs) (2–4). This modification was originally identified as a nuclear event on histone proteins and has been long appreciated for its role in epigenetic and DNA-dependent processes. With the help of a growing number of large-scale acetylation studies, it has become evident that lysine acetylation is ubiquitous, also occurring on cytoplasmic and mitochondrial proteins and has a role in signaling, metabolism, and immunity (1, 4–6). Therefore, the examination of lysine acetylation on nonhistone proteins has gained a prominent role in PTM analysis.To date, the identification of large numbers of acetylation sites has been challenging because of the substoichiometric nature of this modification (7, 8). Additionally, global acetylation is generally less abundant than phosphorylation and ubiquitylation (1). The introduction of antibodies specific for lysine acetylation has significantly improved the ability to enrich and identify thousands of sites (9–14). A landmark study by Choudhary et al. used anti-Kac antibodies to globally map 3600 lysine acetylation sites on 1750 proteins, thereby demonstrating the feasibility of profiling the acetylome (10). A more recent study by Lundby et al. investigated the function and distribution of acetylation sites in 16 different rat tissues, and identified, in aggregate, 15,474 acetylation sites from 4541 proteins (12).Although anti-acetyl lysine antibodies have been a breakthrough for globally mapping acetylation sites (9–12), it remains a challenge to identify large numbers of lysine acetylation sites from a single sample, as is now routinely possible for phosphorylation and ubiquitylation (13, 15–18). To improve the depth-of-coverage in acetylation profiling experiments there is a clear need for (1) alternative anti-acetyl lysine antibodies with higher specificity, (2) optimized antibody usage parameters, and (3) robust proteomic workflows that permit low to moderate protein input. In this study, we describe a newly commercialized mixture of anti-Kac antibodies and detail a complete proteomic workflow for achieving unprecedented coverage of the acetylome from a single stable isotope labeling by amino acids in cell culture (SILAC) labeled sample as well as isobaric tags for relative and absolute quantitation (iTRAQ)- and tandem mass tag (TMT)-labeled samples.     

Genetic dissection of seed weight by QTL analysis and detection of allelic variation in Indian and east European gene pool lines of <Emphasis Type="Italic">Brassica juncea</Emphasis>

Key message

Seed weight QTL identified in different populations were synthesized into consensus QTL which were shown to harbor candidate genes by in silico mapping. Allelic variation inferred would be useful in breeding B. juncea lines with high seed weight.

Abstract

Seed weight is an important yield influencing trait in oilseed Brassicas and is a multigenic trait. Among the oilseed Brassicas, Brassica juncea harbors the maximum phenotypic variation wherein thousand seed weight varies from around 2.0 g to more than 7.0 g. In this study, we have undertaken quantitative trait locus/quantitative trait loci (QTL) analysis of seed weight in B. juncea using four bi-parental doubled-haploid populations. These four populations were derived from six lines (three Indian and three east European lines) with parental phenotypic values for thousand seed weight ranging from 2.0 to 7.6 g in different environments. Multi-environment QTL analysis of the four populations identified a total of 65 QTL ranging from 10 to 25 in each population. Meta-analysis of these component QTL of the four populations identified six ‘consensus’ QTL (C-QTL) in A3, A7, A10 and B3 by merging 33 of the 65 component Tsw QTL from different bi-parental populations. Allelic diversity analysis of these six C-QTL showed that Indian lines, Pusajaikisan and Varuna, hold the most positive allele in all the six C-QTL. In silico mapping of candidate genes with the consensus QTL localized 11 genes known to influence seed weight in Arabidopsis thaliana and also showed conserved crucifer blocks harboring seed weight QTL between the A subgenomes of B. juncea and B. rapa. These findings pave the way for a better understanding of the genetics of seed weight in the oilseed crop B. juncea and reveal the scope available for improvement of seed weight through marker-assisted breeding.