Factors That Affect Large Subunit Ribosomal DNA Amplicon Sequencing Studies of Fungal Communities: Classification Method, Primer Choice, and Error

Nuclear large subunit ribosomal DNA is widely used in fungal phylogenetics and to an increasing extent also amplicon-based environmental sequencing. The relatively short reads produced by next-generation sequencing, however, makes primer choice and sequence error important variables for obtaining accurate taxonomic classifications. In this simulation study we tested the performance of three classification methods: 1) a similarity-based method (BLAST + Metagenomic Analyzer, MEGAN); 2) a composition-based method (Ribosomal Database Project naïve Bayesian classifier, NBC); and, 3) a phylogeny-based method (Statistical Assignment Package, SAP). We also tested the effects of sequence length, primer choice, and sequence error on classification accuracy and perceived community composition. Using a leave-one-out cross validation approach, results for classifications to the genus rank were as follows: BLAST + MEGAN had the lowest error rate and was particularly robust to sequence error; SAP accuracy was highest when long LSU query sequences were classified; and, NBC runs significantly faster than the other tested methods. All methods performed poorly with the shortest 50–100 bp sequences. Increasing simulated sequence error reduced classification accuracy. Community shifts were detected due to sequence error and primer selection even though there was no change in the underlying community composition. Short read datasets from individual primers, as well as pooled datasets, appear to only approximate the true community composition. We hope this work informs investigators of some of the factors that affect the quality and interpretation of their environmental gene surveys

Next-generation RNA sequencing elucidates transcriptomic signatures of pathophysiologic nerve regeneration

Abstract The cellular and molecular underpinnings of Wallerian degeneration have been robustly explored in laboratory models of successful nerve regeneration. In contrast, there is limited interrogation of failed regeneration, which is the challenge facing clinical practice. Specifically, we lack insight on the pathophysiologic mechanisms that lead to the formation of neuromas-in-continuity (NIC). To address this knowledge gap, we have developed and validated a novel basic science model of rapid-stretch nerve injury, which provides a biofidelic injury with NIC development and incomplete neurologic recovery. In this study, we applied next-generation RNA sequencing to elucidate the temporal transcriptional landscape of pathophysiologic nerve regeneration. To corroborate genetic analysis, nerves were subject to immunofluorescent staining for transcripts representative of the prominent biological pathways identified. Pathophysiologic nerve regeneration produces substantially altered genetic profiles both temporally and in the mature neuroma microenvironment, in contrast to the coordinated genetic signatures of Wallerian degeneration and successful regeneration. To our knowledge, this study presents as the first transcriptional study of NIC pathophysiology and has identified cellular death, fibrosis, neurodegeneration, metabolism, and unresolved inflammatory signatures that diverge from pathways elaborated by traditional models of successful nerve regeneration

miRNA-1 promotes acute myeloid leukemia cell pathogenesis through metabolic regulation

Acute myeloid leukemia (AML) is a heterogeneous and deadly disease characterized by uncontrolled expansion of malignant blasts. Altered metabolism and dysregulated microRNA (miRNA) expression profiles are both characteristic of AML. However, there is a paucity of studies exploring how changes in the metabolic state of the leukemic cells regulate miRNA expression leading to altered cellular behavior. Here, we blocked pyruvate entry into mitochondria by deleting the Mitochondria Pyruvate Carrier (MPC1) gene in human AML cell lines, which decreased Oxidative Phosphorylation (OXPHOS). This metabolic shift also led to increased expression of miR-1 in the human AML cell lines tested. AML patient sample datasets showed that higher miR-1 expression correlates with reduced survival. Transcriptional and metabolic profiling of miR-1 overexpressing AML cells revealed that miR-1 increased OXPHOS, along with key metabolites that fuel the TCA cycle such as glutamine and fumaric acid. Inhibition of glutaminolysis decreased OXPHOS in miR-1 overexpressing MV4-11 cells, highlighting that miR-1 promotes OXPHOS through glutaminolysis. Finally, overexpression of miR-1 in AML cells exacerbated disease in a mouse xenograft model. Together, our work expands current knowledge within the field by uncovering novel connections between AML cell metabolism and miRNA expression that facilitates disease progression. Further, our work points to miR-1 as a potential new therapeutic target that may be used to disrupt AML cell metabolism and thus pathogenesis in the clinic