Comparative Genomics of Early-Diverging Brucella Strains Reveals a Novel Lipopolysaccharide Biosynthesis Pathway

Brucella species are Gram-negative bacteria that infect mammals. Recently, two unusual strains (Brucella inopinata BO1(T) and B. inopinata-like BO2) have been isolated from human patients, and their similarity to some atypical brucellae isolated from Australian native rodent species was noted. Here we present a phylogenomic analysis of the draft genome sequences of BO1(T) and BO2 and of the Australian rodent strains 83-13 and NF2653 that shows that they form two groups well separated from the other sequenced Brucella spp. Several important differences were noted. Both BO1(T) and BO2 did not agglutinate significantly when live or inactivated cells were exposed to monospecific A and Mantisera against O-side chain sugars composed of N-formyl-perosamine. While BO1(T) maintained the genes required to synthesize a typical Brucella O-antigen, BO2 lacked many of these genes but still produced a smooth LPS (lipopolysaccharide). Most missing genes were found in the wbk region involved in O-antigen synthesis in classic smooth Brucella spp. In their place, BO2 carries four genes that other bacteria use for making a rhamnose-based O-antigen. Electrophoretic, immunoblot, and chemical analyses showed that BO2 carries an antigenically different O-antigen made of repeating hexose-rich oligosaccharide units that made the LPS water-soluble, which contrasts with the homopolymeric O-antigen of other smooth brucellae that have a phenol-soluble LPS. The results demonstrate the existence of a group of early-diverging brucellae with traits that depart significantly from those of the Brucella species described thus far. IMPORTANCE This report examines differences between genomes from four new Brucella strains and those from the classic Brucella spp. Our results show that the four new strains are outliers with respect to the previously known Brucella strains and yet are part of the genus, forming two new clades. The analysis revealed important information about the evolution and survival mechanisms of Brucella species, helping reshape our knowledge of this important zoonotic pathogen. One discovery of special importance is that one of the strains, BO2, produces an O-antigen distinct from any that has been seen in any other Brucella isolates to date.

Polymorphic toxin systems: Comprehensive characterization of trafficking modes, processing, mechanisms of action, immunity and ecology using comparative genomics

Background: Proteinaceous toxins are observed across all levels of inter-organismal and intra-genomic conflicts. These include recently discovered prokaryotic polymorphic toxin systems implicated in intra-specific conflicts. They are characterized by a remarkable diversity of C-terminal toxin domains generated by recombination with standalone toxin-coding cassettes. Prior analysis revealed a striking diversity of nuclease and deaminase domains among the toxin modules. We systematically investigated polymorphic toxin systems using comparative genomics, sequence and structure analysis. Results: Polymorphic toxin systems are distributed across all major bacterial lineages and are delivered by at least eight distinct secretory systems. In addition to type-II, these include type-V, VI, VII (ESX), and the poorly characterized "Photorhabdus virulence cassettes (PVC)", PrsW-dependent and MuF phage-capsid-like systems. We present evidence that trafficking of these toxins is often accompanied by autoproteolytic processing catalyzed by HINT, ZU5, PrsW, caspase-like, papain-like, and a novel metallopeptidase associated with the PVC system. We identified over 150 distinct toxin domains in these systems. These span an extraordinary catalytic spectrum to include 23 distinct clades of peptidases, numerous previously unrecognized versions of nucleases and deaminases, ADP-ribosyltransferases, ADP ribosyl cyclases, RelA/SpoT-like nucleotidyltransferases, glycosyltranferases and other enzymes predicted to modify lipids and carbohydrates, and a pore-forming toxin domain. Several of these toxin domains are shared with host-directed effectors of pathogenic bacteria. Over 90 families of immunity proteins might neutralize anywhere between a single to at least 27 distinct types of toxin domains. In some organisms multiple tandem immunity genes or immunity protein domains are organized into polyimmunity loci or polyimmunity proteins. Gene-neighborhood-analysis of polymorphic toxin systems predicts the presence of novel trafficking-related components, and also the organizational logic that allows toxin diversification through recombination. Domain architecture and protein-length analysis revealed that these toxins might be deployed as secreted factors, through directed injection, or via inter-cellular contact facilitated by filamentous structures formed by RHS/YD, filamentous hemagglutinin and other repeats. Phyletic pattern and life-style analysis indicate that polymorphic toxins and polyimmunity loci participate in cooperative behavior and facultative 'cheating' in several ecosystems such as the human oral cavity and soil. Multiple domains from these systems have also been repeatedly transferred to eukaryotes and their viruses, such as the nucleo-cytoplasmic large DNA viruses. Conclusions: Along with a comprehensive inventory of toxins and immunity proteins, we present several testable predictions regarding active sites and catalytic mechanisms of toxins, their processing and trafficking and their role in intra-specific and inter-specific interactions between bacteria. These systems provide insights regarding the emergence of key systems at different points in eukaryotic evolution, such as ADP ribosylation, interaction of myosin VI with cargo proteins, mediation of apoptosis, hyphal heteroincompatibility, hedgehog signaling, arthropod toxins, cell-cell interaction molecules like teneurins and different signaling messengers.

Regulatory variation in a TBX5 enhancer leads to isolated congenital heart disease

Recent studies have identified the genetic underpinnings of a growing number of diseases through targeted exome sequencing. However, this strategy ignores the large component of the genome that does not code for proteins, but is nonetheless biologically functional. To address the possible involvement of regulatory variation in congenital heart diseases (CHDs), we searched for regulatory mutations impacting the activity of TBX5, a dosage-dependent transcription factor with well-defined roles in the heart and limb development that has been associated with the HoltOram syndrome (hearthand syndrome), a condition that affects 1/100 000 newborns. Using a combination of genomics, bioinformatics and mouse genetic engineering, we scanned approximate to 700 kb of the TBX5 locus in search of cis-regulatory elements. We uncovered three enhancers that collectively recapitulate the endogenous expression pattern of TBX5 in the developing heart. We re-sequenced these enhancer elements in a cohort of non-syndromic patients with isolated atrial and/or ventricular septal defects, the predominant cardiac defects of the HoltOram syndrome, and identified a patient with a homozygous mutation in an enhancer approximate to 90 kb downstream of TBX5. Notably, we demonstrate that this single-base-pair mutation abrogates the ability of the enhancer to drive expression within the heart in vivo using both mouse and zebrafish transgenic models. Given the population-wide frequency of this variant, we estimate that 1/100 000 individuals would be homozygous for this variant, highlighting that a significant number of CHD associated with TBX5 dysfunction might arise from non-coding mutations in TBX5 heart enhancers, effectively decoupling the heart and hand phenotypes of the HoltOram syndrome.

Assessing the gain of biological data integration in gene networks inference

Background: A current challenge in gene annotation is to define the gene function in the context of the network of relationships instead of using single genes. The inference of gene networks (GNs) has emerged as an approach to better understand the biology of the system and to study how several components of this network interact with each other and keep their functions stable. However, in general there is no sufficient data to accurately recover the GNs from their expression levels leading to the curse of dimensionality, in which the number of variables is higher than samples. One way to mitigate this problem is to integrate biological data instead of using only the expression profiles in the inference process. Nowadays, the use of several biological information in inference methods had a significant increase in order to better recover the connections between genes and reduce the false positives. What makes this strategy so interesting is the possibility of confirming the known connections through the included biological data, and the possibility of discovering new relationships between genes when observed the expression data. Although several works in data integration have increased the performance of the network inference methods, the real contribution of adding each type of biological information in the obtained improvement is not clear. Methods: We propose a methodology to include biological information into an inference algorithm in order to assess its prediction gain by using biological information and expression profile together. We also evaluated and compared the gain of adding four types of biological information: (a) protein-protein interaction, (b) Rosetta stone fusion proteins, (c) KEGG and (d) KEGG+GO. Results and conclusions: This work presents a first comparison of the gain in the use of prior biological information in the inference of GNs by considering the eukaryote (P. falciparum) organism. Our results indicates that information based on direct interaction can produce a higher improvement in the gain than data about a less specific relationship as GO or KEGG. Also, as expected, the results show that the use of biological information is a very important approach for the improvement of the inference. We also compared the gain in the inference of the global network and only the hubs. The results indicates that the use of biological information can improve the identification of the most connected proteins.

Whole genome sequencing analysis of Plasmodium vivax using whole genome capture

Background: Malaria caused by Plasmodium vivax is an experimentally neglected severe disease with a substantial burden on human health. Because of technical limitations, little is known about the biology of this important human pathogen. Whole genome analysis methods on patient-derived material are thus likely to have a substantial impact on our understanding of P. vivax pathogenesis and epidemiology. For example, it will allow study of the evolution and population biology of the parasite, allow parasite transmission patterns to be characterized, and may facilitate the identification of new drug resistance genes. Because parasitemias are typically low and the parasite cannot be readily cultured, on-site leukocyte depletion of blood samples is typically needed to remove human DNA that may be 1000X more abundant than parasite DNA. These features have precluded the analysis of archived blood samples and require the presence of laboratories in close proximity to the collection of field samples for optimal pre-cryopreservation sample preparation. Results: Here we show that in-solution hybridization capture can be used to extract P. vivax DNA from human contaminating DNA in the laboratory without the need for on-site leukocyte filtration. Using a whole genome capture method, we were able to enrich P. vivax DNA from bulk genomic DNA from less than 0.5% to a median of 55% (range 20%-80%). This level of enrichment allows for efficient analysis of the samples by whole genome sequencing and does not introduce any gross biases into the data. With this method, we obtained greater than 5X coverage across 93% of the P. vivax genome for four P. vivax strains from Iquitos, Peru, which is similar to our results using leukocyte filtration (greater than 5X coverage across 96% of the genome). Conclusion: The whole genome capture technique will enable more efficient whole genome analysis of P. vivax from a larger geographic region and from valuable archived sample collections.

Whole-genome sequencing of the efficient industrial fuel-ethanol fermentative Saccharomyces cerevisiae strain CAT-1

The Saccharomyces cerevisiae strains widely used for industrial fuel-ethanol production have been developed by selection, but their underlying beneficial genetic polymorphisms remain unknown. Here, we report the draft whole-genome sequence of the S. cerevisiae strain CAT-1, which is a dominant fuel-ethanol fermentative strain from the sugarcane industry in Brazil. Our results indicate that strain CAT-1 is a highly heterozygous diploid yeast strain, and the similar to 12-Mb genome of CAT-1, when compared with the reference S228c genome, contains similar to 36,000 homozygous and similar to 30,000 heterozygous single nucleotide polymorphisms, exhibiting an uneven distribution among chromosomes due to large genomic regions of loss of heterozygosity (LOH). In total, 58 % of the 6,652 predicted protein-coding genes of the CAT-1 genome constitute different alleles when compared with the genes present in the reference S288c genome. The CAT-1 genome contains a reduced number of transposable elements, as well as several gene deletions and duplications, especially at telomeric regions, some correlated with several of the physiological characteristics of this industrial fuel-ethanol strain. Phylogenetic analyses revealed that some genes were likely associated with traits important for bioethanol production. Identifying and characterizing the allelic variations controlling traits relevant to industrial fermentation should provide the basis for a forward genetics approach for developing better fermenting yeast strains.

Two new species of Hudsonimyia Roback, 1979 (Diptera: Chironomidae: Tanypodinae) from Neotropical Region unveiled by morphology and DNA barcoding

Two new species of Hudsonimyia Roback, 1979 (Diptera: Chironomidae: Tanypodinae) are described and illustrated as male, pupa and larva. The generic diagnosis of pupa is emended and keys to males, pupae and larvae of known species are provided. The different life stages for one of the described species were associated by DNA barcodes.

Diversification of hAT transposase paralogues in the sugarcane genome

Transposons are abundant components of eukaryotic genomes, and play important role in genome evolution. The knowledge about these elements should contribute to the understanding of their impact on the host genomes. The hAT transposon superfamily is one of the best characterized superfamilies in diverse organisms, nevertheless, a detailed study of these elements was never carried in sugarcane. To address this question we analyzed 32 cDNAs similar to that of hAT superfamily of transposons previously identified in the sugarcane transcriptome. Our results revealed that these hAT-like transposases cluster in one highly homogeneous and other more heterogeneous lineage. We present evidences that support the hypothesis that the highly homogeneous group is a domesticated transposase while the remainder of the lineages are composed of transposon units. The first is common to grasses, clusters significantly with domesticated transposases from Arabidopsis, rice and sorghum and is expressed in different tissues of two sugarcane cultivars analyzed. In contrast, the more heterogeneous group represents at least two transposon lineages. We recovered five genomic versions of one lineage, characterizing a novel transposon family with conserved DDE motif, named SChAT. These results indicate the presence of at least three distinct lineages of hAT-like transposase paralogues in sugarcane genome, including a novel transposon family described in Saccharum and a domesticated transposase. Taken together, these findings permit to follow the diversification of some hAT transposase paralogues in sugarcane, aggregating knowledge about the co-evolution of transposons and their host genomes.

Analysis of plant LTR-retrotransposons at the fine-scale family level reveals individual molecular patterns

Background: Sugarcane is an important crop worldwide for sugar production and increasingly, as a renewable energy source. Modern cultivars have polyploid, large complex genomes, with highly unequal contributions from ancestral genomes. Long Terminal Repeat retrotransposons (LTR-RTs) are the single largest components of most plant genomes and can substantially impact the genome in many ways. It is therefore crucial to understand their contribution to the genome and transcriptome, however a detailed study of LTR-RTs in sugarcane has not been previously carried out. Results: Sixty complete LTR-RT elements were classified into 35 families within four Copia and three Gypsy lineages. Structurally, within lineages elements were similar, between lineages there were large size differences. FISH analysis resulted in the expected pattern of Gypsy/heterochromatin, Copia/euchromatin, but in two lineages there was localized clustering on some chromosomes. Analysis of related ESTs and RT-PCR showed transcriptional variation between tissues and families. Four distinct patterns were observed in sRNA mapping, the most unusual of which was that of Ale1, with very large numbers of 24nt sRNAs in the coding region. The results presented support the conclusion that distinct small RNA-regulated pathways in sugarcane target the lineages of LTR-RT elements. Conclusions: Individual LTR-RT sugarcane families have distinct structures, and transcriptional and regulatory signatures. Our results indicate that in sugarcane individual LTR-RT families have distinct behaviors and can potentially impact the genome in diverse ways. For instance, these transposable elements may affect nearby genes by generating a diverse set of small RNA's that trigger gene silencing mechanisms. There is also some evidence that ancestral genomes contribute significantly different element numbers from particular LTR-RT lineages to the modern sugarcane cultivar genome.

Genome Sequence of Exiguobacterium antarcticum B7, Isolated from a Biofilm in Ginger Lake, King George Island, Antarctica

Exiguobacterium antarcticum is a psychotropic bacterium isolated for the first time from microbial mats of Lake Fryxell in Antarctica. Many organisms of the genus Exiguobacterium are extremophiles and have properties of biotechnological interest, e. g., the capacity to adapt to cold, which make this genus a target for discovering new enzymes, such as lipases and proteases, in addition to improving our understanding of the mechanisms of adaptation and survival at low temperatures. This study presents the genome of E. antarcticum B7, isolated from a biofilm sample of Ginger Lake on King George Island, Antarctic peninsula.

Whole blood genome-wide gene expression profile in males after prolonged wakefulness and sleep recovery

Pellegrino R, Sunaga DY, Guindalini C, Martins RC, Mazzotti DR, Wei Z, Daye ZJ, Andersen ML, Tufik S. Whole blood genome-wide gene expression profile in males after prolonged wakefulness and sleep recovery. Physiol Genomics 44: 1003-1012, 2012. First published September 4, 2012; doi: 10.1152/physiolgenomics.00058.2012.-Although the specific functions of sleep have not been completely elucidated, the literature has suggested that sleep is essential for proper homeostasis. Sleep loss is associated with changes in behavioral, neurochemical, cellular, and metabolic function as well as impaired immune response. Using high-resolution microarrays we evaluated the gene expression profiles of healthy male volunteers who underwent 60 h of prolonged wakefulness (PW) followed by 12 h of sleep recovery (SR). Peripheral whole blood was collected at 8 am in the morning before the initiation of PW (Baseline), after the second night of PW, and one night after SR. We identified over 500 genes that were differentially expressed. Notably, these genes were related to DNA damage and repair and stress response, as well as diverse immune system responses, such as natural killer pathways including killer cell lectin-like receptors family, as well as granzymes and T-cell receptors, which play important roles in host defense. These results support the idea that sleep loss can lead to alterations in molecular processes that result in perturbation of cellular immunity, induction of inflammatory responses, and homeostatic imbalance. Moreover, expression of multiple genes was downregulated following PW and upregulated after SR compared with PW, suggesting an attempt of the body to re-establish internal homeostasis. In silico validation of alterations in the expression of CETN3, DNAJC, and CEACAM genes confirmed previous findings related to the molecular effects of sleep deprivation. Thus, the present findings confirm that the effects of sleep loss are not restricted to the brain and can occur intensely in peripheral tissues.

Comparative Genome Analysis of Trichophyton rubrum and Related Dermatophytes Reveals Candidate Genes Involved in Infection

The major cause of athlete's foot is Trichophyton rubrum, a dermatophyte or fungal pathogen of human skin. To facilitate molecular analyses of the dermatophytes, we sequenced T. rubrum and four related species, Trichophyton tonsurans, Trichophyton equinum, Microsporum canis, and Microsporum gypseum. These species differ in host range, mating, and disease progression. The dermatophyte genomes are highly colinear yet contain gene family expansions not found in other human-associated fungi. Dermatophyte genomes are enriched for gene families containing the LysM domain, which binds chitin and potentially related carbohydrates. These LysM domains differ in sequence from those in other species in regions of the peptide that could affect substrate binding. The dermatophytes also encode novel sets of fungus-specific kinases with unknown specificity, including nonfunctional pseudokinases, which may inhibit phosphorylation by competing for kinase sites within substrates, acting as allosteric effectors, or acting as scaffolds for signaling. The dermatophytes are also enriched for a large number of enzymes that synthesize secondary metabolites, including dermatophyte-specific genes that could synthesize novel compounds. Finally, dermatophytes are enriched in several classes of proteases that are necessary for fungal growth and nutrient acquisition on keratinized tissues. Despite differences in mating ability, genes involved in mating and meiosis are conserved across species, suggesting the possibility of cryptic mating in species where it has not been previously detected. These genome analyses identify gene families that are important to our understanding of how dermatophytes cause chronic infections, how they interact with epithelial cells, and how they respond to the host immune response. IMPORTANCE Athlete's foot, jock itch, ringworm, and nail infections are common fungal infections, all caused by fungi known as dermatophytes (fungi that infect skin). This report presents the genome sequences of Trichophyton rubrum, the most frequent cause of athlete's foot, as well as four other common dermatophytes. Dermatophyte genomes are enriched for four gene classes that may contribute to the ability of these fungi to cause disease. These include (i) proteases secreted to degrade skin; (ii) kinases, including pseudokinases, that are involved in signaling necessary for adapting to skin; (iii) secondary metabolites, compounds that act as toxins or signals in the interactions between fungus and host; and (iv) a class of proteins (LysM) that appear to bind and mask cell wall components and carbohydrates, thus avoiding the host's immune response to the fungi. These genome sequences provide a strong foundation for future work in understanding how dermatophytes cause disease.

Identifying regulational alterations in gene regulatory networks by state space representation of vector autoregressive models and variational annealing

Background: In the analysis of effects by cell treatment such as drug dosing, identifying changes on gene network structures between normal and treated cells is a key task. A possible way for identifying the changes is to compare structures of networks estimated from data on normal and treated cells separately. However, this approach usually fails to estimate accurate gene networks due to the limited length of time series data and measurement noise. Thus, approaches that identify changes on regulations by using time series data on both conditions in an efficient manner are demanded. Methods: We propose a new statistical approach that is based on the state space representation of the vector autoregressive model and estimates gene networks on two different conditions in order to identify changes on regulations between the conditions. In the mathematical model of our approach, hidden binary variables are newly introduced to indicate the presence of regulations on each condition. The use of the hidden binary variables enables an efficient data usage; data on both conditions are used for commonly existing regulations, while for condition specific regulations corresponding data are only applied. Also, the similarity of networks on two conditions is automatically considered from the design of the potential function for the hidden binary variables. For the estimation of the hidden binary variables, we derive a new variational annealing method that searches the configuration of the binary variables maximizing the marginal likelihood. Results: For the performance evaluation, we use time series data from two topologically similar synthetic networks, and confirm that our proposed approach estimates commonly existing regulations as well as changes on regulations with higher coverage and precision than other existing approaches in almost all the experimental settings. For a real data application, our proposed approach is applied to time series data from normal Human lung cells and Human lung cells treated by stimulating EGF-receptors and dosing an anticancer drug termed Gefitinib. In the treated lung cells, a cancer cell condition is simulated by the stimulation of EGF-receptors, but the effect would be counteracted due to the selective inhibition of EGF-receptors by Gefitinib. However, gene expression profiles are actually different between the conditions, and the genes related to the identified changes are considered as possible off-targets of Gefitinib. Conclusions: From the synthetically generated time series data, our proposed approach can identify changes on regulations more accurately than existing methods. By applying the proposed approach to the time series data on normal and treated Human lung cells, candidates of off-target genes of Gefitinib are found. According to the published clinical information, one of the genes can be related to a factor of interstitial pneumonia, which is known as a side effect of Gefitinib.

Mutations in SRCAP, Encoding SNF2-Related CREBBP Activator Protein, Cause Floating-Harbor Syndrome

Floating-Harbor syndrome (FHS) is a rare condition characterized by short stature, delayed osseous maturation, expressive-language deficits, and a distinctive facial appearance. Occurrence is generally sporadic, although parent-to-child transmission has been reported on occasion. Employing whole-exome sequencing, we identified heterozygous truncating mutations in SRCAP in five unrelated individuals with sporadic MS. Sanger sequencing identified mutations in SRCAP in eight more affected persons. Mutations were de novo in all six instances in which parental DNA was available. SRCAP is an SNF2-related chromatin-remodeling factor that serves as a coactivator for CREB-binding protein (CREBBP, better known as CBP, the major cause of Rubinstein-Taybi syndrome [RTS]). Five SRCAP mutations, two of which are recurrent, were identified; all are tightly clustered within a small (111 codon) region of the final exon. These mutations are predicted to abolish three C-terminal AT-hook DNA-binding motifs while leaving the CBP-binding and ATPase domains intact. Our findings show that SRCAP mutations are the major cause of FHS and offer an explanation for the clinical overlap between FHS and RTS.

Strain-specific polyketide synthase genes of Aspergillus niger

In silico comparison of 34 putative pks genes in Aspergillus niger strain CBS 513.88 versus A. niger strain ATCC 1015 genome revealed significant nucleotide identity (>95% covering a minimum of 99% of the gene sequence) for 31 of these genes (approximately 91%). A. niger CBS 513.88 harbors three putative pks genes (An01g01130, An11g05940, and An15g07920), for which nucleotide identity was not found in A. niger ATCC 1015. To compare the results of the in silico analysis with the in vivo situation, experimental data were obtained for a large number of A. niger strains obtained from different substrates and geographical regions. Three putative Os genes that were found to be variable between the two A. niger strains using bioinformatics tools were in fact strain-specific genes based on experimental data. The PCR amplification signals for the An01g01130, An11g05940, and An15g07920 pks genes were detected in only 97%, 71%, and 26% of the strains, respectively. Southern blot analyses confirmed the PCR data. Because one of the strain-specific pits genes (An15g07920) is located in a putative ochratoxin cluster, we focused our investigation on that region. We assessed the ochratoxin production capability of the 119 A. niger strains and found a positive association between the presence of this pia gene and the capability of the respective strain to produce ochratoxin. (C) 2012 Elsevier B.V. All rights reserved.