Cytotoxicity of isolated compounds from Picrasma crenata (Vell.) Engl. in animal tumor cell (HTC)

The study aim was to evaluate the cytotoxic activity, using the MTT test [3-(4,5-Dimethilthiazol-2-yl)-2,5-diphenil tetrazolium bromide], from the crude extract of Picrasma crenata (Pau Tenente) and its isolated compounds, quassin and parain, in culture of rat liver tumor cells (HTC). The test was carried out exposing the cells for 24, 48 and 72 hours to concentrations of 5, 10, 50, 100, 200, 300, 400, 500 and 1000 μg of crude extract of Pau Tenente/mL of culture medium and 1, 5, 10, 15, 20, 40, 60, 80 and 100 μg of quassin or parain compounds/mL of culture medium. The absorbances averages results obtained showed that the crude extract did not present cytotoxicity for the HTC cells in all the concentrations and evaluated times. For quassin, the concentrations of 80 and 100 μg/mL were cytotoxic, after 72 hours of treatment. For parain, the concentrations of 1, 5, 20, 40, 60, 80 and 100 µg/mL, in 72 hours, were cytotoxic, revealing a new activity for this compound. Thus, the results demonstrate a first indication of the cytotoxic activity of compounds quassin and parain, adding an important social and economic value to them, and may have application in future research and in pharmaceutical industry.

Small and mighty: adaptation of superphylum Patescibacteria to groundwater environment drives their genome simplicity

BACKGROUND

The newly defined superphylum Patescibacteria such as Parcubacteria (OD1) and Microgenomates (OP11) has been found to be prevalent in groundwater, sediment, lake, and other aquifer environments. Recently increasing attention has been paid to this diverse superphylum including > 20 candidate phyla (a large part of the candidate phylum radiation, CPR) because it refreshed our view of the tree of life. However, adaptive traits contributing to its prevalence are still not well known.

RESULTS

Here, we investigated the genomic features and metabolic pathways of Patescibacteria in groundwater through genome-resolved metagenomics analysis of > 600 Gbp sequence data. We observed that, while the members of Patescibacteria have reduced genomes (~ 1 Mbp) exclusively, functions essential to growth and reproduction such as genetic information processing were retained. Surprisingly, they have sharply reduced redundant and nonessential functions, including specific metabolic activities and stress response systems. The Patescibacteria have ultra-small cells and simplified membrane structures, including flagellar assembly, transporters, and two-component systems. Despite the lack of CRISPR viral defense, the bacteria may evade predation through deletion of common membrane phage receptors and other alternative strategies, which may explain the low representation of prophage proteins in their genomes and lack of CRISPR. By establishing the linkages between bacterial features and the groundwater environmental conditions, our results provide important insights into the functions and evolution of this CPR group.

CONCLUSIONS

We found that Patescibacteria has streamlined many functions while acquiring advantages such as avoiding phage invasion, to adapt to the groundwater environment. The unique features of small genome size, ultra-small cell size, and lacking CRISPR of this large lineage are bringing new understandings on life of Bacteria. Our results provide important insights into the mechanisms for adaptation of the superphylum in the groundwater environments, and demonstrate a case where less is more, and small is mighty.

Construction of Viable Soil Defined Media Using Quantitative Metabolomics Analysis of Soil Metabolites

Exometabolomics enables analysis of metabolite utilization of low molecular weight organic substances by soil bacteria. Environmentally-based defined media are needed to examine ecologically relevant patterns of substrate utilization. Here, we describe an approach for the construction of defined media using untargeted characterization of water soluble soil microbial metabolites from a saprolite soil collected from the Oak Ridge Field Research Center (ORFRC). To broadly characterize metabolites, both liquid chromatography mass spectrometry (LC/MS) and gas chromatography mass spectrometry (GC/MS) were used. With this approach, 96 metabolites were identified, including amino acids, amino acid derivatives, sugars, sugar alcohols, mono- and di-carboxylic acids, nucleobases, and nucleosides. From this pool of metabolites, 25 were quantified. Molecular weight cut-off filtration determined the fraction of carbon accounted for by the quantified metabolites and revealed that these soil metabolites have an uneven quantitative distribution (e.g., trehalose accounted for 9.9% of the <1 kDa fraction). This quantitative information was used to formulate two soil defined media (SDM), one containing 23 metabolites (SDM1) and one containing 46 (SDM2). To evaluate the viability of the SDM, we examined the growth of 30 phylogenetically diverse soil bacterial isolates from the ORFRC field site. The simpler SDM1 supported the growth of 13 isolates while the more complex SDM2 supported 15 isolates. To investigate SDM1 substrate preferences, one isolate, Pseudomonas corrugata strain FW300-N2E2 was selected for a time-series exometabolomics analysis. Interestingly, it was found that this organism preferred lower-abundance substrates such as guanine, glycine, proline and arginine and glucose and did not utilize the more abundant substrates maltose, mannitol, trehalose and uridine. These results demonstrate the viability and utility of using exometabolomics to construct a tractable environmentally relevant media. We anticipate that this approach can be expanded to other environments to enhance isolation and characterization of diverse microbial communities.

Oxidative status of the myocardium in response to different intensities of physical training

The intensity of exercise determines the metabolic pathway and the energetic substrate that is spent. Our study sought to identify the effects of different intensities of swimming on myocardial oxidative status and the blood lipid profile. Eighty Wistar rats (male and female) submitted to different intensities of a swimming regimen (low, LS; moderate, MS; or high, HS) for 16 weeks. Samples of blood and myocardium from the left ventricle were collected to determine lipid profiles and oxidative status. Reactive oxygen species (ROS) and antioxidant capacity against peroxyl radicals (ACAP), lipid profiles and lipid peroxidation was analyzed. ROS levels and ACAP were higher in male rats than in female rats overall (p<0.05). However, ACAP in the myocardium was significantly elevated in LS female rats compared to the MS and HS female rats, which had a significantly lower ACAP compared to all other groups. LS and MS training in both sexes and HS training (in females) led to significant decreases in the heart's lipid peroxidation. Amelioration of the lipid profile and reduction in oxidative damage contributed to a physiological state that benefits cardiovascular function in exercised animals. The results show that low and moderate intensity exercise promotes beneficial adaptations.

Natural bacterial communities serve as quantitative geochemical biosensors

Biological sensors can be engineered to measure a wide range of environmental conditions. Here we show that statistical analysis of DNA from natural microbial communities can be used to accurately identify environmental contaminants, including uranium and nitrate at a nuclear waste site. In addition to contamination, sequence data from the 16S rRNA gene alone can quantitatively predict a rich catalogue of 26 geochemical features collected from 93 wells with highly differing geochemistry characteristics. We extend this approach to identify sites contaminated with hydrocarbons from the Deepwater Horizon oil spill, finding that altered bacterial communities encode a memory of prior contamination, even after the contaminants themselves have been fully degraded. We show that the bacterial strains that are most useful for detecting oil and uranium are known to interact with these substrates, indicating that this statistical approach uncovers ecologically meaningful interactions consistent with previous experimental observations. Future efforts should focus on evaluating the geographical generalizability of these associations. Taken as a whole, these results indicate that ubiquitous, natural bacterial communities can be used as in situ environmental sensors that respond to and capture perturbations caused by human impacts. These in situ biosensors rely on environmental selection rather than directed engineering, and so this approach could be rapidly deployed and scaled as sequencing technology continues to become faster, simpler, and less expensive.

IMPORTANCE

Here we show that DNA from natural bacterial communities can be used as a quantitative biosensor to accurately distinguish unpolluted sites from those contaminated with uranium, nitrate, or oil. These results indicate that bacterial communities can be used as environmental sensors that respond to and capture perturbations caused by human impacts.

Analysis of power transfer on multicore fibers with long-period gratings

The use of long-period gratings (LPGs) to distribute optical power from one core to all the cores in a multicore fiber (MCF) is theoretically analyzed. Simple analytical expressions that describe the mode power's evolution along the LPGs are derived from the coupled mode equations. This study demonstrated the power transfer between cores in a MCF promoted by identical LPGs. Moreover, with this technique, the pump signal can be distributed to all the cores without interfering with the transmission signals.

Effect of calcium, bicarbonate, and albumin on capacitation-related events in equine sperm

Repeatable methods for IVF have not been established in the horse, reflecting the failure of standard capacitating media to induce changes required for fertilization capacity in equine sperm. One important step in capacitation is membrane cholesterol efflux, which in other species is triggered by cholesterol oxidation and is typically enhanced using albumin as a sterol acceptor. We incubated equine sperm in the presence of calcium, BSA, and bicarbonate, alone or in combination. Bicarbonate induced an increase in reactive oxygen species (ROS) that was abolished by the addition of calcium or BSA. Bicarbonate induced protein tyrosine phosphorylation (PY), even in the presence of calcium or BSA. Incubation at high pH enhanced PY but did not increase ROS production. Notably, no combination of these factors was associated with significant cholesterol efflux, as assessed by fluorescent quantitative cholesterol assay and confirmed by filipin staining. By contrast, sperm treated with methyl-β-cyclodextrin showed a significant reduction in cholesterol levels, but no significant increase in PY or ROS. Presence of BSA increased sperm binding to bovine zonae pellucidae in all three stallions. These results show that presence of serum albumin is not associated with a reduction in membrane cholesterol levels in equine sperm, highlighting the failure of equine sperm to exhibit core capacitation-related changes in a standard capacitating medium. These data indicate an atypical relationship among cholesterol efflux, ROS production, and PY in equine sperm. Our findings may help to elucidate factors affecting failure of equine IVF under standard conditions.

Advances in monitoring environmental microbes

Culture-independent approaches, such as next-generation sequencing and microarray-based tools, provide insight into the identity and functional diversity of microbial communities. Although these approaches are potentially powerful tools in understanding microbial structure and function, there are a number of limitations that may bias conclusions. In order to mitigate these biases, an understanding of potential biases within each stage of the experimental process is necessary. This review focuses on the biases associated with sample collection, nucleic acid extraction, processing, sequencing analyses, and Chip technologies used in microbial ecology studies.

Halting the fuse discharge propagation using optical fiber microwires

We report and analyze the halting of the fuse effect propagation in optical fiber microwires. The increase of the mode field diameter in the tapered region decreases the optical intensity resulting in the extinction of the fuse effect. This fiber element presents a low insertion loss and can be introduced in the optical network in order to protect the active equipment from the damage caused by the fuse effect.

SPICE: discovery of phenotype-determining component interplays

Background

A latent behavior of a biological cell is complex. Deriving the underlying simplicity, or the fundamental rules governing this behavior has been the Holy Grail of systems biology. Data-driven prediction of the system components and their component interplays that are responsible for the target system’s phenotype is a key and challenging step in this endeavor.

Results

The proposed approach, which we call System Phenotype-related Interplaying Components Enumerator (Spice), iteratively enumerates statistically significant system components that are hypothesized (1) to play an important role in defining the specificity of the target system’s phenotype(s); (2) to exhibit a functionally coherent behavior, namely, act in a coordinated manner to perform the phenotype-specific function; and (3) to improve the predictive skill of the system’s phenotype(s) when used collectively in the ensemble of predictive models. Spice can be applied to both instance-based data and network-based data. When validated, Spice effectively identified system components related to three target phenotypes: biohydrogen production, motility, and cancer. Manual results curation agreed with the known phenotype-related system components reported in literature. Additionally, using the identified system components as discriminatory features improved the prediction accuracy by 10% on the phenotype-classification task when compared to a number of state-of-the-art methods applied to eight benchmark microarray data sets.

Conclusion

We formulate a problem—enumeration of phenotype-determining system component interplays—and propose an effective methodology (Spice) to address this problem. Spice improved identification of cancer-related groups of genes from various microarray data sets and detected groups of genes associated with microbial biohydrogen production and motility, many of which were reported in literature. Spice also improved the predictive skill of the system’s phenotype determination compared to individual classifiers and/or other ensemble methods, such as bagging, boosting, random forest, nearest shrunken centroid, and random forest variable selection method.

NIBBS-search for fast and accurate prediction of phenotype-biased metabolic systems

Understanding of genotype-phenotype associations is important not only for furthering our knowledge on internal cellular processes, but also essential for providing the foundation necessary for genetic engineering of microorganisms for industrial use (e.g., production of bioenergy or biofuels). However, genotype-phenotype associations alone do not provide enough information to alter an organism's genome to either suppress or exhibit a phenotype. It is important to look at the phenotype-related genes in the context of the genome-scale network to understand how the genes interact with other genes in the organism. Identification of metabolic subsystems involved in the expression of the phenotype is one way of placing the phenotype-related genes in the context of the entire network. A metabolic system refers to a metabolic network subgraph; nodes are compounds and edges labels are the enzymes that catalyze the reaction. The metabolic subsystem could be part of a single metabolic pathway or span parts of multiple pathways. Arguably, comparative genome-scale metabolic network analysis is a promising strategy to identify these phenotype-related metabolic subsystems. Network Instance-Based Biased Subgraph Search (NIBBS) is a graph-theoretic method for genome-scale metabolic network comparative analysis that can identify metabolic systems that are statistically biased toward phenotype-expressing organismal networks. We set up experiments with target phenotypes like hydrogen production, TCA expression, and acid-tolerance. We show via extensive literature search that some of the resulting metabolic subsystems are indeed phenotype-related and formulate hypotheses for other systems in terms of their role in phenotype expression. NIBBS is also orders of magnitude faster than MULE, one of the most efficient maximal frequent subgraph mining algorithms that could be adjusted for this problem. Also, the set of phenotype-biased metabolic systems output by NIBBS comes very close to the set of phenotype-biased subgraphs output by an exact maximally-biased subgraph enumeration algorithm ( MBS-Enum ). The code (NIBBS and the module to visualize the identified subsystems) is available at http://freescience.org/cs/NIBBS.

Efficient α, β-motif finder for identification of phenotype-related functional modules

Background

Microbial communities in their natural environments exhibit phenotypes that can directly cause particular diseases, convert biomass or wastewater to energy, or degrade various environmental contaminants. Understanding how these communities realize specific phenotypic traits (e.g., carbon fixation, hydrogen production) is critical for addressing health, bioremediation, or bioenergy problems.

Results

In this paper, we describe a graph-theoretical method for in silico prediction of the cellular subsystems that are related to the expression of a target phenotype. The proposed (α, β)-motif finder approach allows for identification of these phenotype-related subsystems that, in addition to metabolic subsystems, could include their regulators, sensors, transporters, and even uncharacterized proteins. By comparing dozens of genome-scale networks of functionally associated proteins, our method efficiently identifies those statistically significant functional modules that are in at least α networks of phenotype-expressing organisms but appear in no more than β networks of organisms that do not exhibit the target phenotype. It has been shown via various experiments that the enumerated modules are indeed related to phenotype-expression when tested with different target phenotypes like hydrogen production, motility, aerobic respiration, and acid-tolerance.

Conclusion

Thus, we have proposed a methodology that can identify potential statistically significant phenotype-related functional modules. The functional module is modeled as an (α, β)-clique, where α and β are two criteria introduced in this work. We also propose a novel network model, called the two-typed, divided network. The new network model and the criteria make the problem tractable even while very large networks are being compared. The code can be downloaded from http://www.freescience.org/cs/ABClique/

DENSE: efficient and prior knowledge-driven discovery of phenotype-associated protein functional modules

Background

Identifying cellular subsystems that are involved in the expression of a target phenotype has been a very active research area for the past several years. In this paper, cellular subsystem refers to a group of genes (or proteins) that interact and carry out a common function in the cell. Most studies identify genes associated with a phenotype on the basis of some statistical bias, others have extended these statistical methods to analyze functional modules and biological pathways for phenotype-relatedness. However, a biologist might often have a specific question in mind while performing such analysis and most of the resulting subsystems obtained by the existing methods might be largely irrelevant to the question in hand. Arguably, it would be valuable to incorporate biologist's knowledge about the phenotype into the algorithm. This way, it is anticipated that the resulting subsytems would not only be related to the target phenotype but also contain information that the biologist is likely to be interested in.

Results

In this paper we introduce a fast and theoretically guranteed method called DENSE (Dense and ENriched Subgraph Enumeration) that can take in as input a biologist's prior knowledge as a set of query proteins and identify all the dense functional modules in a biological network that contain some part of the query vertices. The density (in terms of the number of network egdes) and the enrichment (the number of query proteins in the resulting functional module) can be manipulated via two parameters γ and μ, respectively.

Conclusion

This algorithm has been applied to the protein functional association network of Clostridium acetobutylicum ATCC 824, a hydrogen producing, acid-tolerant organism. The algorithm was able to verify relationships known to exist in literature and also some previously unknown relationships including those with regulatory and signaling functions. Additionally, we were also able to hypothesize that some uncharacterized proteins are likely associated with the target phenotype. The DENSE code can be downloaded from http://www.freescience.org/cs/DENSE/

The use of dried blood spots for assessing antibody response to hepatitis A virus after natural infection and vaccination

During recent years, vaccination against hepatitis A has been implemented in several countries. It is expected that the increase in mass vaccination against hepatitis A will eventually result in a decreased prevalence of anti-HAV antibodies in the general population. For this reason, a suitable clinical sample for diagnosis of hepatitis A must be sufficiently sensitive to enable detection of lower antibodies titers. In this study, the feasibility of using dried blood spots (DBS) was assessed for the detection of anti-HAV antibodies after a natural infection and vaccination. Seventy-four DBS and paired plasma samples were obtained from a group of college students for a cross-sectional hepatitis A seroepidemiological study. Forty-six students seronegative for anti-HAV were selected randomly and immunized with an inactivated hepatitis A vaccine using an 0-6 month schedule. Seroconversion was monitored in paired plasma and DBS samples 6 months after the first dose followed by a period of 8 and 24 months after the second dose. A strong correlation between OD/CO rates of paired plasma and DBS samples for the detection of anti-HAV was observed. The sensitivity and specificity of the DBS compared with plasma for the detection of anti-HAV antibodies after natural infection was 100%. The sensitivity of DBS in samples collected 24 months after the second dose of hepatitis A vaccine was 95.4%. The results showed that DBS samples can be used for the detection of anti-HAV antibodies both after natural infection or vaccination.

The GHEP-EMPOP collaboration on mtDNA population data--A new resource for forensic casework

Mitochondrial DNA (mtDNA) population data for forensic purposes are still scarce for some populations, which may limit the evaluation of forensic evidence especially when the rarity of a haplotype needs to be determined in a database search. In order to improve the collection of mtDNA lineages from the Iberian and South American subcontinents, we here report the results of a collaborative study involving nine laboratories from the Spanish and Portuguese Speaking Working Group of the International Society for Forensic Genetics (GHEP-ISFG) and EMPOP. The individual laboratories contributed population data that were generated throughout the past 10 years, but in the majority of cases have not been made available to the scientific community. A total of 1019 haplotypes from Iberia (Basque Country, 2 general Spanish populations, 2 North and 1 Central Portugal populations), and Latin America (3 populations from São Paulo) were collected, reviewed and harmonized according to defined EMPOP criteria. The majority of data ambiguities that were found during the reviewing process (41 in total) were transcription errors confirming that the documentation process is still the most error-prone stage in reporting mtDNA population data, especially when performed manually. This GHEP–EMPOP collaboration has significantly improved the quality of the individual mtDNA datasets and adds mtDNA population data as valuable resource to the EMPOP database (www.empop.org).

Quantification of fecal estradiol and progesterone metabolites in Syrian hamsters (Mesocricetus auratus)

Alternative methods to the utilization of laboratory animal blood and its by-products are particularly attractive, especially regarding hamsters due to their small size and difficulties in obtaining serial blood samples. Steroid hormone metabolite quantification in feces, widely used in studies of free-ranging or intractable animals, is a non-invasive, non-stressor, economical, and animal saving technique which allows longitudinal studies by permitting frequent sampling of the same individual. The present study was undertaken to determine the suitability of this method for laboratory animals. Estradiol and progesterone metabolites were quantified by radioimmunoassay in feces of intact, sexually mature female Syrian hamsters during the estrous cycle (control) and in feces of superovulated females. Metabolites were extracted by fecal dilution in ethanol and quantified by solid phase radioimmunoassay. Median estrogen and progesterone concentrations were 9.703 and 180.74 ng/g feces in the control group, respectively. Peaks of estrogen (22.44 +/- 4.54 ng/g feces) and progesterone (655.95 +/- 129.93 ng/g feces) mean fecal concentrations respectively occurred 12 h before and immediately after ovulation, which is easily detected in this species by observation of a characteristic vaginal postovulatory discharge. Median estrogen and progesterone concentrations (28.159 and 586.57 ng/g feces, respectively) were significantly higher in superovulated animal feces (P < 0.0001). The present study demonstrated that it is possible to monitor ovarian activity in Syrian hamsters non-invasively by measuring fecal estradiol and progesterone metabolites. This technique appears to be a quite encouraging method for the development of new endocrinologic studies on laboratory animals.

Anti-CagA antibodies in Helicobacter pylori-positive patients and blood donors from Nigeria

The prevalence of antibodies to CagA protein was evaluated in 174 Helicobacter pylori-positive. subjects: 110 patients submitted to upper gastrointestinal endoscopy and 64 male blood donors. The patients were from different regions of Nigeria: Jos, North, Benue,West and East and the blood donors were from Jos. Sera were assayed for anti-CagA antibodies using Helicobacter p120, CagA ELISA (Viva Diagnostika, Hürth, Germany). Anti-CagA antibodies were detected in 104 (94.5%) patients and in 61 (95.3%) blood donors (P=1.0). Patients from the Benue region presented a lower frequency of anti-CagA antibodies than patients from the other regions (P=0.0004). When the subjects were stratified by age, a significant increase in IgG concentration was observed among the men (P=0.03) but not among the women (P=0.57) or among the blood donors (P=0.83). In conclusion, similarly toAsian countries, CagA-positive H. pylori infection is highly frequent in Nigeria.

iceA genotypes of Helicobacter pylori strains isolated from Brazilian children and adults

Data concerning the geographic distribution of iceA alleles are scarce, and information on the association of the gene with the disease is rare and still controversial. Furthermore, no such study has been developed in Brazil, where duodenal ulcer and gastric adenocarcinoma are very common. We investigated, by PCR, the frequency of iceA alleles and cagA status in Helicobacter pylori strains isolated from 142 patients (62 children and 80 adults; 66 female; mean age, 30.0 years; age range, 3 to 78 years) with gastritis, duodenal ulcer, or gastric adenocarcinoma. iceA was identified in bacterium samples obtained from all patients. Eleven (7.7%) of them were infected with multiple strains. Among the patients with nonmixed infection, iceA2 allele was detected in 118 (90.1%). iceA2 allele was associated with ulcer (P = 0.02) and with carcinoma (P = 0.001). iceA2 amplicons of 229, 334, or 549 bp were detected, but none of them was associated with the patient's disorder. iceA2 strains were more frequent in patients older than 7 years (P = 0.001). The gene was also more frequent in strains obtained from males (P = 0.02). cagA was more common in strains obtained from carcinoma (P = 0.0008) and ulcer patients (P < 0.006). cagA-positive strains were more frequent in children older than 7 years (P < 0.003). No association between cagA status and sex was found (P = 0.28). In conclusion, we think iceA should not be used as a reliable marker for predicting the clinical outcome of H. pylori infection.

Leptin levels, beta-cell function, and insulin sensitivity in families with congenital and acquired generalized lipoatropic diabetes

Lipoatropic diabetes (LD) designates a group of syndromes characterized by diabetes mellitus with marked insulin resistance and either a localized or generalized absence of adipose tissue. In this study, we evaluated plasma leptin levels in subjects with congenital generalized lipoatropic diabetes (CGLD, n = 11) or acquired generalized lipoatropic diabetes (AGLD, n = 11), and assessed correlations between leptin levels and estimations of insulin secretion and insulin sensitivity using homeostasis model assessment (HOMA). Leptin levels were 0.86 +/- 0.32, 1.76 +/- 0.78, and 6.9 +/- 4.4 ng/mL in subjects with CGLD, AGLD, and controls (n = 19), respectively (ANOVA P < 0.0001). Specific insulin levels were 154 +/- 172, 177 +/- 137 and 43 +/- 22 pmol/L, respectively (P < 0.0001). Insulin sensitivity was significantly decreased in both groups with LD (P < 0.0001), whereas HOMA beta-cell function was not significantly different when compared with controls. Leptin levels were significantly correlated with body mass index, insulin levels, and HOMA beta-cell function, and inversely correlated with insulin sensitivity in control subjects but not in subjects with generalized LD. In conclusion, decreased leptin levels were observed in subjects with generalized LD, with a trend towards lower levels in the acquired than in the congenital form (P = 0.06). The temporal relationship between the decrease in leptin levels and the development of lipoatrophy should be investigated in at-risk young relatives of subjects with the acquired forms to assess the usefulness of leptin levels as a marker of lipoatrophy.