bioarchaeological and paleopathological scholarship.
Nutrient availability and ratios can play an important role in shaping microbial communities of freshwater ecosystems. The Cuatro Ciénegas Basin (CCB) in Mexico is a desert oasis where, perhaps paradoxically, high microbial diversity coincides with extreme oligotrophy. To better understand the effects of nutrients on microbial communities in CCB, a mesocosm experiment was implemented in a stoichiometrically imbalanced pond, Lagunita, which has an average TN:TP ratio of 122 (atomic). The experiment had four treatments, each with five spatial replicates – unamended controls and three fertilization treatments with different nitrogen:phosphorus (N:P) regimes (P only, N:P = 16 and N:P = 75 by atoms). In the water column, quantitative PCR of the 16S rRNA gene indicated that P enrichment alone favored proliferation of bacterial taxa with high rRNA gene copy number, consistent with a previously hypothesized but untested connection between rRNA gene copy number and P requirement. Bacterial and microbial eukaryotic community structure was investigated by pyrosequencing of 16S and 18S rRNA genes from the planktonic and surficial sediment samples. Nutrient enrichment shifted the composition of the planktonic community in a treatment-specific manner and promoted the growth of previously rare bacterial taxa at the expense of the more abundant, potentially endemic, taxa. The eukaryotic community was highly enriched with phototrophic populations in the fertilized treatment. The sediment microbial community exhibited high beta diversity among replicates within treatments, which obscured any changes due to fertilization. Overall, these results showed that nutrient stoichiometry can be an important factor in shaping microbial community structure.
Background:
Many pharmaceutical drugs are known to be ineffective or have negative side effects in a substantial proportion of patients. Genomic advances are revealing that some non-synonymous single nucleotide variants (nsSNVs) may cause differences in drug efficacy and side effects. Therefore, it is desirable to evaluate nsSNVs of interest in their ability to modulate the drug response.
Results:
We found that the available data on the link between drug response and nsSNV is rather modest. There were only 31 distinct drug response-altering (DR-altering) and 43 distinct drug response-neutral (DR-neutral) nsSNVs in the whole Pharmacogenomics Knowledge Base (PharmGKB). However, even with this modest dataset, it was clear that existing bioinformatics tools have difficulties in correctly predicting the known DR-altering and DR-neutral nsSNVs. They exhibited an overall accuracy of less than 50%, which was not better than random diagnosis. We found that the underlying problem is the markedly different evolutionary properties between positions harboring nsSNVs linked to drug responses and those observed for inherited diseases. To solve this problem, we developed a new diagnosis method, Drug-EvoD, which was trained on the evolutionary properties of nsSNVs associated with drug responses in a sparse learning framework. Drug-EvoD achieves a TPR of 84% and a TNR of 53%, with a balanced accuracy of 69%, which improves upon other methods significantly.
Conclusions:
The new tool will enable researchers to computationally identify nsSNVs that may affect drug responses. However, much larger training and testing datasets are needed to develop more reliable and accurate tools.