Strategies for genetic conservation of trees in the Peruvian Amazon

Forestry practices and high rates of land clearance for agriculture are causing genetic erosion of valuable tree species in the Peruvian Amazon, thereby endangering the economic sustainability of rural communities and limiting Peru's opportunities for the development of new timber and non-timber forest products. The potential utility and limitations of six low-input interventions to help forestall further genetic erosion in the region are discussed, with a focus on local community involvement. Improved agroforestry systems may help reduce deforestation by increasing farm productivity, although methods to increase the currently low adoption rate of these technologies need to be developed. Use of strategic tree domestication techniques can also improve farm productivity and prevent inadvertent genetic drift and inbreeding associated with traditional domestication practices, although to have a major impact, current programs need to be extended across the region. Woodlot forestry could supplant selective extraction of timber and offers an attractive opportunity for poverty alleviation if appropriate credit and land tenure policies can be developed. However, it may also result in increased deforestation if activities on public land cannot be controlled. The implementation of improved seed collection systems and simple seed transfer guidelines would help to reduce the collection of seed of poor quality and low genetic diversity, and avoid maladapted plantings, although such programs are difficult to monitor and seed costs may increase. Strategic identification and design of in situ conservation areas would help to ensure the viability of conserved populations, but requires the forfeiture of significant revenue from timber concessions.     

Immunohistochemical analysis of pRb2/p130, VEGF, EZH2, p53, p16(INK4A), p27(KIP1), p21(WAF1), Ki-67 expression patterns in gastric cancer

Although the considerable progress against gastric cancer, it remains a complex lethal disease defined by peculiar histological and molecular features. The purpose of the present study was to investigate pRb2/p130, VEGF, EZH2, p53, p16(INK4A), p27(KIP1), p21(WAF1), Ki-67 expressions, and analyze their possible correlations with clinicopathological factors. The expression patterns were examined by immunohistochemistry in 47 patients, 27 evaluated of intestinal-type, and 20 of diffuse-type, with a mean follow up of 56 months and by Western blot in AGS, N87, KATO-III, and YCC-2, -3, -16 gastric cell lines. Overall, stomach cancer showed EZH2 correlated with high levels of p53, Ki-67, and cytoplasmic pRb2/p130 (P < 0.05, and P < 0.01, respectively). Increased expression of EZH2 was found in the intestinal-type and correlated with the risk of distant metastasis (P < 0.05 and P < 0.01, respectively), demonstrating that this protein may have a prognostic value in this type of cancer. Interestingly, a strong inverse correlation was observed between p27(KIP1) expression levels and the risk of advanced disease and metastasis (P < 0.05), and a positive correlation between the expression levels of p21(WAF1) and low-grade (G1) gastric tumors (P < 0.05), confirming the traditionally accepted role for these tumor-suppressor genes in gastric cancer. Finally, a direct correlation was found between the expression levels of nuclear pRb2/p130 and low-grade (G1) gastric tumors that was statistically significant (P < 0.05). Altogether, these data may help shed some additional light on the pathogenetic mechanisms related to the two main gastric cancer histotypes and their invasive potentials.     

High expression level of a gene coding for a chloroplastic amino acid selective channel protein is correlated to cold acclimation in cereals

A cold-regulated gene (cor tmc-ap3) coding for a putative chloroplastic amino acid selective channel protein was isolated from cold-treated barley leaves combining the differential display and the 5-RACE techniques. Cor tmc-ap3 is expressed at low level under normal growing temperature, and its expression is strongly enhanced after cold treatment. A positive correlation between the expression of cor tmc-ap3 and frost tolerance was found both among barley cultivars and among cereal species. The COR TMC-AP3 protein was expressed in vitro, purified and used to raise a polyclonal antibody. Western analysis showed that the cor tmc-ap3 gene product is localized to the chloroplastic outer envelope fraction, supporting its putative function. The frost-resistant winter cultivar Onice accumulated COR TMC-AP3 more rapidly and at a higher level than the frost-susceptible spring cultivar Gitane. After 28 days of cold acclimation the winter cultivar had about 2-fold more protein than the spring genotype. All these results suggest that an increased amount of a chloroplastic amino acid selective channel protein could be required for cold acclimation in cereals. Hypotheses about the role of COR TMC-AP3 during the hardening process are discussed.     

Backbone dynamics of alamethicin bound to lipid membranes: spin-echo electron paramagnetic resonance of TOAC-spin labels

Alamethicin F50/5 is a hydrophobic peptide that is devoid of charged residues and that induces voltage-dependent ion channels in lipid membranes. The peptide backbone is likely to be involved in the ion conduction pathway. Electron spin-echo spectroscopy of alamethicin F50/5 analogs in which a selected Aib residue (at position n = 1, 8, or 16) is replaced by the TOAC amino-acid spin label was used to study torsional dynamics of the peptide backbone in association with phosphatidylcholine bilayer membranes. Rapid librational motions of limited angular amplitude were observed at each of the three TOAC sites by recording echo-detected spectra as a function of echo delay time, 2τ. Simulation of the time-resolved spectra, combined with conventional EPR measurements of the librational amplitude, shows that torsional fluctuations of the peptide backbone take place on the subnanosecond to nanosecond timescale, with little temperature dependence. Associated fluctuations in polar fields from the peptide could facilitate ion permeation.     

Validation of the Macrophyte Quality Index (MaQI) set up to assess the ecological status of Italian marine transitional environments

The paper couples the results obtained by applying the expert and the rapid Macrophyte Quality Indices set up to assess the ecological status of the Italian transitional environments according to the requirements by the Water Framework Directive (2000/60/CE). The indices were validated by comparing the composition of the macrophyte assemblages and the values of some bio-physico-chemical parameters of the water column of 20 stations of the Venice lagoon sampled monthly for one year between 2003 and 2005. In 5 stations out of the 20, the ones which fall within the 5 classes of ecological status suggested by the Water Framework Directive, sedimentation rates, sediment grain-size, and nutrient and pollutant (metals, Polychloro-Dibenzo-Dioxins/Furans, Polycyclic Aromatic Hydrocarbons, Pesticides and Polychlorinated Biphenils) concentrations in surface sediments were also determined. Results showed strong relationships between the trends of these environmental parameters and the composition and structure of macrophyte associations, as well as with the Macrophyte Quality Index assessment. Chlorophyceae showed a trend opposite to Rhodophyceae whose presence was concentrated in oxygenated and transparent environments. Chlorophyceae and the species characterised by low scores prevailed in turbid areas where nutrient and pollutant concentrations were high. Results allowed the identification of the conditions of the “reference sites” (confinement areas and sites with high water renewal) and the integration of the dichotomic key used for the application of the R-MaQI. Handling editor: S. M. Thomaz     

A field guide to cultivating computational biology

Evolving in sync with the computation revolution over the past 30 years, computational biology has emerged as a mature scientific field. While the field has made major contributions toward improving scientific knowledge and human health, individual computational biology practitioners at various institutions often languish in career development. As optimistic biologists passionate about the future of our field, we propose solutions for both eager and reluctant individual scientists, institutions, publishers, funding agencies, and educators to fully embrace computational biology. We believe that in order to pave the way for the next generation of discoveries, we need to improve recognition for computational biologists and better align pathways of career success with pathways of scientific progress. With 10 outlined steps, we call on all adjacent fields to move away from the traditional individual, single-discipline investigator research model and embrace multidisciplinary, data-driven, team science.

Do you want to attract computational biologists to your project or to your department? Despite the major contributions of computational biology, those attempting to bridge the interdisciplinary gap often languish in career advancement, publication, and grant review. Here, sixteen computational biologists around the globe present "A field guide to cultivating computational biology," focusing on solutions.

Biology in the digital era requires computation and collaboration. A modern research project may include multiple model systems, use multiple assay technologies, collect varying data types, and require complex computational strategies, which together make effective design and execution difficult or impossible for any individual scientist. While some labs, institutions, funding bodies, publishers, and other educators have already embraced a team science model in computational biology and thrived [1–7], others who have not yet fully adopted it risk severely lagging behind the cutting edge. We propose a general solution: “deep integration” between biology and the computational sciences. Many different collaborative models can yield deep integration, and different problems require different approaches (Fig 1).Open in a separate windowFig 1Supporting interdisciplinary team science will accelerate biological discoveries.Scientists who have little exposure to different fields build silos, in which they perform science without external input. To solve hard problems and to extend your impact, collaborate with diverse scientists, communicate effectively, recognize the importance of core facilities, and embrace research parasitism. In biologically focused parasitism, wet lab biologists use existing computational tools to solve problems; in computationally focused parasitism, primarily dry lab biologists analyze publicly available data. Both strategies maximize the use and societal benefit of scientific data.In this article, we define computational science extremely broadly to include all quantitative approaches such as computer science, statistics, machine learning, and mathematics. We also define biology broadly, including any scientific inquiry pertaining to life and its many complications. A harmonious deep integration between biology and computer science requires action—we outline 10 immediate calls to action in this article and aim our speech directly at individual scientists, institutions, funding agencies, and publishers in an attempt to shift perspectives and enable action toward accepting and embracing computational biology as a mature, necessary, and inevitable discipline (Box 1).Box 1. Ten calls to action for individual scientists, funding bodies, publishers, and institutions to cultivate computational biology. Many actions require increased funding support, while others require a perspective shift. For those actions that require funding, we believe convincing the community of need is the first step toward agencies and systems allocating sufficient support

1. Respect collaborators’ specific research interests and motivationsProblem: Researchers face conflicts when their goals do not align with collaborators. For example, projects with routine analyses provide little benefit for computational biologists.Solution: Explicit discussion about interests/expertise/goals at project onset.Opportunity: Clearly defined expectations identify gaps, provide commitment to mutual benefit.
2. Seek necessary input during project design and throughout the project life cycleProblem: Modern research projects require multiple experts spanning the project’s complexity.Solution: Engage complementary scientists with necessary expertise throughout the entire project life cycle.Opportunity: Better designed and controlled studies with higher likelihood for success.
3. Provide and preserve budgets for computational biologists’ workProblem: The perception that analysis is “free” leads to collaborator budget cuts.Solution: When budget cuts are necessary, ensure that they are spread evenly.Opportunity: More accurate, reproducible, and trustworthy computational analyses.
4. Downplay publication author order as an evaluation metric for computational biologistsProblem: Computational biologist roles on publications are poorly understood and undervalued.Solution: Journals provide more equitable opportunities, funding bodies and institutions improve understanding of the importance of team science, scientists educate each other.Opportunity: Engage more computational biologist collaborators, provide opportunities for more high-impact work.
5. Value software as an academic productProblem: Software is relatively undervalued and can end up poorly maintained and supported, wasting the time put into its creation.Solution: Scientists cite software, and funding bodies provide more software funding opportunities.Opportunity: More high-quality maintainable biology software will save time, reduce reimplementation, and increase analysis reproducibility.
6. Establish academic structures and review panels that specifically reward team scienceProblem: Current mechanisms do not consistently reward multidisciplinary work.Solution: Separate evaluation structures to better align peer review to reward indicators of team science.Opportunity: More collaboration to attack complex multidisciplinary problems.
7. Develop and reward cross-disciplinary training and mentoringProblem: Academic labs and institutions are often insufficiently equipped to provide training to tackle the next generation of biological problems, which require computational skills.Solution: Create better training programs aligned to necessary on-the-job skills with an emphasis on communication, encourage wet/dry co-mentorship, and engage younger students to pursue computational biology.Opportunity: Interdisciplinary students uncover important insights in their own data.
8. Support computing and experimental infrastructure to empower computational biologistsProblem: Individual computational labs often fund suboptimal cluster computing systems and lack access to data generation facilities.Solution: Institutions can support centralized compute and engage core facilities to provide data services.Opportunity: Time and cost savings for often overlooked administrative tasks.
9. Provide incentives and mechanisms to share open data to empower discovery through reanalysisProblem: Data are often siloed and have untapped potential.Solution: Provide institutional data storage with standardized identifiers and provide separate funding mechanisms and publishing venues for data reuse.Opportunity: Foster new breed of researchers, “research parasites,” who will integrate multimodal data and enhance mechanistic insights.
10. Consider infrastructural, ethical, and cultural barriers to clinical data accessProblem: Identifiable health data, which include sensitive information that must be kept hidden, are distributed and disorganized, and thus underutilized.Solution: Leadership must enforce policies to share deidentifiable data with interoperable metadata identifiers.Opportunity: Derive new insights from multimodal data integration and build datasets with increased power to make biological discoveries.

     

Two-dimensional mapping as a tool for classification of green coffee bean species

Two species of the genus Coffea, Coffea arabica (Colombia) and Coffea canephora (Indiano Robusta) were analysed by two-dimensional (2-D) maps in order to obtain fingerprints of the expressed polypeptide chains and to determine which ones would characterize the two species. Green beans were milled under liquid nitrogen. A dry powder was produced by three different extraction protocols aimed at eliminating interfering substances (polyphenols). A reduced powder was produced by two successive extractions performed in acetone. Trichloroacetic acid (TCA; 10% w/v) and beta-mercaptoethanol (0.07% v/v) in acetone were used for the first extraction (a) and 10% w/v TCA in acetone was used for the second extraction (b). Proteins were then solubilized in a solution (40 microL per 1 mg powder) containing 7 M urea, 2 M thiourea, 3% w/v 3-(3-cholamidopropyldimethyl-amino)-1-propanesulfate, 1% v/v carrier ampholytes, 40 mM Tris, 5 mM tributylphosphine and 10 mM acrylamide as alkylating agent. Following incubation at room temperature for 1 hour and centrifugation (7000 rpm for 20 minutes), the supernatant was used for 2-D electrophoresis. The proteins were revealed by Sypro Ruby staining. Master maps of the five replicas of each species were compared by PDQuest analysis. The results of this differential proteome analysis were: sixteen proteins were expressed solely in C. canephora (var. Indiano Robusta) and five proteins were only found in C. arabica (var. Colombia). Another eight proteins were up-regulated in C. canephora (var. Indiano Robusta) in comparison to C. arabica (var. Colombia) and one was down-regulated in the same comparison. A number of these polypeptide chains were further characterized by mass spectrometry in the matrix-assisted laser desorption/ionisation-time of flight mode. Additionally, considering the low number of protein sequences of Coffea present in the databases we also investigated some spots with a more powerful tool, reversed phase-high-performance liquid chromatography-electrospray ionisation-tandem mass spectrometry, thus obtaining an internal peptide sequence. The general properties of the identified proteins are presented and discussed.     

AtLACS7 interacts with the TPR domains of the PTS1 receptor PEX5

Long-chain acyl-CoA synthetases (LACSs) activate fatty acids for further metabolism and are encoded by a multi-gene family in Arabidopsis. AtLACS6 possesses a type 2 (PTS2) peroxisomal targeting sequence, whilst AtLACS7 has both a type 1 and type 2 peroxisomal targeting sequence. AtLACS7 was used as bait in a yeast two-hybrid screen. Multiple clones of the PTS1 receptor PEX5 were isolated. Quantitative beta-galactosidase assay indicated that full-length PEX5 interacts with AtLACS7 with higher affinity than the TPR domains alone. The interaction between PEX5 and AtLACS7 was confirmed by co-immunoprecipitation and shown to be specific for the PTS1, therefore the AtLACS7 PTS1 is accessible to bind PEX5 in the full-length AtLACS7 protein. The expression profile of AtLACS6, AtLACS7, AtPEX5, and AtPEX7 revealed that AtLACS6 and 7 have distinct patterns of expression and we speculate that the possession of two targeting signals may be advantageous for the import of AtLACS7 when receptors may be limiting.