Changes in Proteome and Protein Phosphorylation Reveal the Protective Roles of Exogenous Nitrogen in Alleviating Cadmium Toxicity in Poplar Plants

Phytoremediation soil polluted by cadmium has drawn worldwide attention. However, how to improve the efficiency of plant remediation of cadmium contaminated soil remains unknown. Previous studies showed that nitrogen (N) significantly enhances cadmium uptake and accumulation in poplar plants. In order to explore the important role of nitrogen in plants’ responses to cadmium stress, this study investigates the poplar proteome and phosphoproteome difference between Cd stress and Cd + N treatment. In total, 6573 proteins were identified, and 5838 of them were quantified. With a fold-change threshold of > 1.3, and a p-value < 0.05, 375 and 108 proteins were up- and down-regulated by Cd stress when compared to the control, respectively. Compared to the Cd stress group, 42 and 89 proteins were up- and down-regulated by Cd + N treatment, respectively. Moreover, 522 and 127 proteins were up- and down-regulated by Cd + N treatment compared to the CK group. In addition, 1471 phosphosites in 721 proteins were identified. Based on a fold-change threshold of > 1.2, and a p-value < 0.05, the Cd stress up-regulated eight proteins containing eight phosphosites, and down-regulated 58 proteins containing 69 phosphosites, whereas N + Cd treatment up-regulated 86 proteins containing 95 phosphosites, and down-regulated 17 proteins containing 17 phosphosites, when compared to Cd stress alone. N + Cd treatment up-regulated 60 proteins containing 74 phosphosites and down-regulated 37 proteins containing 42 phosphosites, when compared to the control. Several putative responses to stress proteins, as well as transcriptional and translational regulation factors, were up-regulated by the addition of exogenous nitrogen following Cd stress. Especially, heat shock protein 70 (HSP70), 14-3-3 protein, peroxidase (POD), zinc finger protein (ZFP), ABC transporter protein, eukaryotic translation initiation factor (elF) and splicing factor 3 B subunit 1-like (SF3BI) were up-regulated by Cd + N treatment at both the proteome and the phosphoproteome levels. Combing the proteomic data and phosphoproteomics data, the mechanism by which exogenous nitrogen can alleviate cadmium toxicity in poplar plants was explained at the molecular level. The results of this study will establish the solid molecular foundation of the phytoremediation method to improve cadmium-contaminated soil.

Gene Expression Profiling of CD34+/Lin- Cells of Patients with Chronic Myeloid Leukemia at Diagnosis and after 12 Months of Nilotinib

Chronic myeloid leukemia (CML) is a disease of stemming from genetic damage to a hematopoietic stem cell. Despite nilotinib being a very effective drug for the treatment of CML, drug resistance can emerge. In the contest of the REL-PhilosoPhi34 study on behalf of the Rete Ematologica Lombarda, we performed an exploratory study aimed to identify the gene expression signature of bone marrow (BM) CD34+/lin- cells of CML patients at diagnosis as well as after 12 months of nilotinib to investigate the genes and pathways responsible for the response or resistance to nilotinib. Microarray experiments were performed using the latest generation Affymetrix GeneChip HTA 2.0 to further investigate genomic complexity. The study was developed in two steps as follows: In the first step we analyzed 30 CML patients and from the comparison between the BM CD34+/lin- cell counts from each patient at diagnosis and after 3 and 6 months of nilotinib, patients were divided into 2 classes: class 1 (n=24) showed highly reduced levels of CD34+/lin- cells while class 2 (n=6) demonstrated increasing levels of CD34+/lin- cells after 3 and 6 months of nilotinib, respectively (Fig.1). The 30 patients can be divided into 6 groups showing different patterns of CD34+/lin- cellularity (Figure 1). Data was preprocessed and normalized using Robust Multi-array Average (RMA) algorithm. The Significant Analysis of Microarrays (SAM) was used to identify genes with statistically significant changes in expression in CML patients. P-values were corrected for multiple testing using false discovery rate. No transcripts were selected as differentially expressed using this threshold. However, if a nominal significance level alpha equal to 0.05 is adopted together with a fold-change threshold equal to 2 (absolute value), 56 transcripts were selected in the comparison between the 2 groups of CML patients. Among them, we focused on NFKBIAgene which was over expressed in class 1 compared to class 2.NFKBIA is involved in 68 pathways regulating apoptosis (PI3K,NF-kB) and encodes IkBα protein belonging to the NF-kB pathway which is a potential downstream target of BCR-ABL1 due to its role in regulating cell survival and proliferation. Of note, 31/56 transcripts are located on chromosome 15 suggesting that this region could be crucial for transcriptional regulation of CML correlated to nilotinib response. The second step analyzed the GEP of CD34+/lin- cells of 8 patients at diagnosis (class 1) vs. the same 8 patients after 12 months of nilotinib (class 2) to investigate the gene expression changes and the pathways induced by nilotinib treatment. Data was preprocessed and analyzed as described above. 247 probes (corresponding to 51 genes and 180 non-annotated transcripts) were selected with a p-value lower than 0.05 after multiple testing correction and using a fold-change threshold equal to 3 (absolute value). Functional enrichment analysis was performed using DAVID and highlighted the following pathways and genes: ¯ Defense response and immune system: CAMP, CRISP3, CYBB, RGS1, CEACAM8, LTF (cell growth and differentiation), MNDA and HP (positive regulation of apoptosis) were over expressed in class 2 with high fold changes of 7.65, 9.95, 4.40, 3.47, 4.28, 3.61, 3.60, 3.95, respectively ¯ Transcriptional regulation and cell cycle: MMP8was under expressed in class 1 with the high fold change of 8,94 ¯ S100A12, S100A8, S100A9 (regulation of the cell cycle and differentiation) were over expressed in class 2 with the FC of 8.68, 3.96, 4.49, respectively ¯ RNA5S-ribosomal pseudogenes 310-311-312-313-314-315-316-317-320-363 were downregulated in class 2 ¯ 10 small-nuclear-RNAs and 11 small-nucleolar RNA were differently deregulated between the 2 classes ¯ APOC1, PLBD1 (lipid metabolism) were overexpressed and underexpressed in class 1, respectively In conclusion, this is the first study of GEP of CD34+/lin- cells with HTA 2.0 which demonstrated that 51 genes mostly involved in immune system, transcriptional regulation and cell cycle were significantly differently expressed from the comparison between CML patients at diagnosis and after 12 month of nilotinib. Ongoing studies are focused on examining the genetic and biologic mechanisms underlying nilotinib response or resistance to predict response or failure providing new insights into the molecular mechanisms in CML. Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.

Assigning Significance in Label-Free Quantitative Proteomics to Include Single-Peptide-Hit Proteins with Low Replicates

When sample replicates are limited in a label-free proteomics experiment, selecting differentially regulated proteins with an assignment of statistical significance remains difficult for proteins with a single-peptide hit or a small fold-change. This paper aims to address this issue. An important component of the approach employed here is to utilize the rule of Minimum number of Permuted Significant Pairings (MPSP) to reduce false positives. The MPSP rule generates permuted sample pairings from limited analytical replicates and simply requires that a differentially regulated protein can be selected only when it is found significant in designated number of permuted sample pairings. Both a power law global error model with a signal-to-noise ratio statistic (PLGEM-STN) and a constant fold-change threshold were initially used to select differentially regulated proteins. But both methods were found not stringent enough to control the false discovery rate to 5% in this study. On the other hand, the combination of the MPSP rule with either of these two methods significantly reduces false positives with little effect on the sensitivity to select differentially regulated proteins including those with a single-peptide hit or with a <2-fold change.