Fungal Bioweathering of Mimetite and a General Geomycological Model for Lead Apatite Mineral Biotransformations

Fungi play important roles in biogeochemical processes such as organic matter decomposition, bioweathering of minerals and rocks, and metal transformations and therefore influence elemental cycles for essential and potentially toxic elements, e.g., P, S, Pb, and As. Arsenic is a potentially toxic metalloid for most organisms and naturally occurs in trace quantities in soil, rocks, water, air, and living organisms. Among more than 300 arsenic minerals occurring in nature, mimetite [Pb₅(AsO₄)₃Cl] is the most stable lead arsenate and holds considerable promise in metal stabilization for in situ and ex situ sequestration and remediation through precipitation, as do other insoluble lead apatites, such as pyromorphite [Pb₅(PO₄)₃Cl] and vanadinite [Pb₅(VO₄)₃Cl]. Despite the insolubility of mimetite, the organic acid-producing soil fungus Aspergillus niger was able to solubilize mimetite with simultaneous precipitation of lead oxalate as a new mycogenic biomineral. Since fungal biotransformation of both pyromorphite and vanadinite has been previously documented, a new biogeochemical model for the biogenic transformation of lead apatites (mimetite, pyromorphite, and vanadinite) by fungi is hypothesized in this study by application of geochemical modeling together with experimental data. The models closely agreed with experimental data and provided accurate simulation of As and Pb complexation and biomineral formation dependent on, e.g., pH, cation-anion composition, and concentration. A general pattern for fungal biotransformation of lead apatite minerals is proposed, proving new understanding of ecological implications of the biogeochemical cycling of component elements as well as industrial applications in metal stabilization, bioremediation, and biorecovery.     

Splenic gene expression profiling in White Leghorn layer inoculated with the Salmonella enterica serovar Enteritidis

Salmonella enterica serovar Enteritidis (SE) is a foodborne pathogen that can threaten human health through contaminated poultry products. Live poultry, chicken eggs and meat are primary sources of human salmonellosis. To understand the genetic resistance of egg‐type chickens in response to SE inoculation, global gene expression in the spleen of 20‐week‐old White Leghorn was measured using the Agilent 4 × 44 K chicken microarray at 7 and 14 days following SE inoculation (dpi). Results showed that there were 1363 genes significantly differentially expressed between inoculated and non‐inoculated groups at 7 dpi (I7/N7), of which 682 were up‐regulated and 681 were down‐regulated genes. By contrast, 688 differentially expressed genes were observed at 14 dpi (I14/N14), of which 371 were up‐regulated genes and 317 were down‐regulated genes. There were 33 and 28 immune‐related genes significantly differentially expressed in the comparisons of I7/N7 and I14/N14 respectively. Functional annotation revealed that several Gene Ontology (GO) terms related to immunity were significantly enriched between the inoculated and non‐inoculated groups at 14 dpi but not at 7 dpi, despite a similar number of immune‐related genes identified between I7/N7 and I14/N14. The immune response to SE inoculation changes with different time points following SE inoculation. The complicated interaction between the immune system and metabolism contributes to the immune responses to SE inoculation of egg‐type chickens at 14 dpi at the onset of lay. GC, TNFSF8, CD86, CD274, BLB1 and BLB2 play important roles in response to SE inoculation. The results from this study will deepen the current understanding of the genetic response of the egg‐type chicken to SE inoculation at the onset of egg laying.     

Focus: A Multifaceted Battle Against Cancer: Extracting Knowledge from Chemical Imaging Data Using Computational Algorithms for Digital Cancer Diagnosis

Fourier transform infrared (FTIR) spectroscopic imaging is an emerging microscopy modality for clinical histopathologic diagnoses as well as for biomedical research. Spectral data recorded in this modality are indicative of the underlying, spatially resolved biochemical composition but need computerized algorithms to digitally recognize and transform this information to a diagnostic tool to identify cancer or other physiologic conditions. Statistical pattern recognition forms the backbone of these recognition protocols and can be used for highly accurate results. Aided by biochemical correlations with normal and diseased states and the power of modern computer-aided pattern recognition, this approach is capable of combating many standing questions of traditional histology-based diagnosis models. For example, a simple diagnostic test can be developed to determine cell types in tissue. As a more advanced application, IR spectral data can be integrated with patient information to predict risk of cancer, providing a potential road to precision medicine and personalized care in cancer treatment. The IR imaging approach can be implemented to complement conventional diagnoses, as the samples remain unperturbed and are not destroyed. Despite high potential and utility of this approach, clinical implementation has not yet been achieved due to practical hurdles like speed of data acquisition and lack of optimized computational procedures for extracting clinically actionable information rapidly. The latter problem has been addressed by developing highly efficient ways to process IR imaging data but remains one that has considerable scope for progress. Here, we summarize the major issues and provide practical considerations in implementing a modified Bayesian classification protocol for digital molecular pathology. We hope to familiarize readers with analysis methods in IR imaging data and enable researchers to develop methods that can lead to the use of this promising technique for digital diagnosis of cancer.     

Effects of experimental warming on survival,phenology, and morphology of an aquatic insect (Odonata)

1. Organisms can respond to changing climatic conditions in multiple ways including changes in phenology, body size or morphology, and range shifts. Understanding how developmental temperatures affect insect life‐history timing and morphology is crucial because body size and morphology affect multiple aspects of life history, including dispersal ability, whereas phenology can shape population performance and community interactions. 2. It was experimentally assessed how developmental temperatures experienced by aquatic larvae affected survival, phenology, and adult morphology of dragonflies [Pachydiplax longipennis (Burmeister)]. Larvae were reared under three environmental temperatures: ambient, +2.5, and +5 °C, corresponding to temperature projections for our study area 50 and 100 years in the future, respectively. Experimental temperature treatments tracked naturally‐occurring variation. 3. Clear effects of temperature were found in the rearing environment on survival and phenology: dragonflies reared at the highest temperatures had the lowest survival rates and emerged from the larval stage approximately 3 weeks earlier than animals reared at ambient temperatures. There was no effect of rearing temperature on overall body size. Although neither the relative wing nor thorax size was affected by warming, a non‐significant trend towards an interaction between sex and warming in relative thorax size suggests that males may be more sensitive to warming than females, a pattern that should be investigated further. 4. Warming strongly affected survival in the larval stage and the phenology of adult emergence. Understanding how warming in the developmental environment affects later life‐history stages is critical to interpreting the consequences of warming for organismal performance.