Comparative landscape dynamics of two anuran species: climate‐driven interaction of local and regional processes

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/117162/1/ecm2009793503.pd

Estimating species relative abundances from museum records

Funding: C.F., U.B. and D.J.R. acknowledge COST Action ‘European Soil-Biology Data Warehouse for Soil Protection’ (EUdaphobase), CA18237, supported by COST (European Cooperation in Science and Technology). AEM thanks the Leverhulme Trust (RPG-2019-401). D.B.B. was supported by an NSF Postdoc Research Fellowship in Biology (NSF 000733206), S.M.R. was supported by an NSERC Discovery Grant Author Contributions, A.V.S. was supported by NSF 1755336, C.S.M was supported by NSF 1398620 and N.J.G was supported by NSF 2019470.1. Dated, geo-referenced museum specimens are a rich data source for reconstructing species' distribution and abundance patterns. However, museum records are potentially biased towards over-representation of rare species, and it is unclear whether museum records can be used to estimate relative abundance in the field. 2. We assembled 17 coupled field and museum datasets to quantitatively compare relative abundance estimates with the Dirichlet distribution. Collectively, these datasets comprise 73,039 museum records and 1,405,316 field observations of 2,240 species. 3. Although museum records of rare species overestimated relative abundance by 1-fold to over 100-fold (median study = 9.0), the relative abundance of species estimated from museum occurrence records was strongly correlated with relative abundance estimated from standardized field surveys (r2 range of 0.10-0.91, median study = 0.43). 4. These analyses provide a justification for estimating species relative abundance with carefully curated museum occurrence records, which may allow for the detection of temporal or spatial shifts in the rank ordering of common and rare species.Publisher PDFPeer reviewe

Universal Ecological Patterns in College Basketball Communities

The rank abundance of common and rare species within ecological communities is remarkably consistent from the tropics to the tundra. This invariant patterning provides one of ecology's most enduring and unified tenets: most species rare and a few very common. Increasingly, attention is focused upon elucidating biological mechanisms that explain these species abundance distributions (SADs), but these evaluations remain controversial. We show that college basketball wins generate SADs just like those observed in ecological communities. Whereas college basketball wins are structured by competitive interactions, the result produces a SAD pattern indistinguishable from random wins. We also show that species abundance data for tropical trees exhibits a significant-digit pattern consistent with data derived from complex structuring forces. These results cast doubt upon the ability of SAD analysis to resolve ecological mechanism, and their patterning may reflect statistical artifact as much as biological processes

Mapping the Binding between the Tetraspanin Molecule (Sjc23) of Schistosoma japonicum and Human Non-Immune IgG

BACKGROUND: Schistosomal parasites can establish parasitization in a human host for decades; evasion of host immunorecognition including surface masking by acquisition of host serum components is one of the strategies explored by the parasites. Parasite molecules anchored on the membrane are the main elements in the interaction. Sjc23, a member of the tetraspanin (TSP) family of Schistosoma japonicum, was previously found to be highly immunogenic and regarded as a vaccine candidate against schistosomiasis. However, studies indicated that immunization with Sjc23 generated rapid antibody responses which were less protective than that with other antigens. The biological function of this membrane-anchored molecule has not been defined after decades of vaccination studies. METHODOLOGY AND PRINCIPAL FINDINGS: In this study, we explored affinity pull-down and peptide competition assays to investigate the potential binding between Sjc23 molecule and human non-immune IgG. We determined that Sjc23 could bind human non-immune IgG and the binding was through the interaction of the large extra-cellular domain (LED) of Sjc23 (named Sjc23-LED) with the Fc domain of human IgG. Sjc23 had no affinity to other immunoglobulin types. Affinity precipitation (pull-down assay) in the presence of overlapping peptides further pinpointed to a 9-amino acid motif within Sjc23-LED that mediated the binding to human IgG. CONCLUSION AND SIGNIFICANCE: S. japonicum parasites cloak themselves through interaction with human non-immune IgG, and a member of the tetraspanin family, Sjc23, mediated the acquisition of human IgG via the interaction of a motif of 9 amino acids with the Fc domain of the IgG molecule. The consequence of this interaction will likely benefit parasitism of S. japonicum by evasion of host immune recognition or immunoresponses. This is the first report that an epitope of schistosomal ligand and its immunoglobulin receptor are defined, which provides further evidence of immune evasion strategy adopted by S. japonicum

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts