RESUMO
Machine learning approaches have been used for the automatic detection of Parkinson's disease with voice recordings being the most used data type due to the simple and non-invasive nature of acquiring such data. Although voice recordings captured via telephone or mobile devices allow much easier and wider access for data collection, current conflicting performance results limit their clinical applicability. This study has two novel contributions. First, we show the reliability of personal telephone-collected voice recordings of the sustained vowel /a/ in natural settings by collecting samples from 50 people with specialist-diagnosed Parkinson's disease and 50 healthy controls and applying machine learning classification with voice features related to phonation. Second, we utilize a novel application of a pre-trained convolutional neural network (Inception V3) with transfer learning to analyze the spectrograms of the sustained vowel from these samples. This approach considers speech intensity estimates across time and frequency scales rather than collapsing measurements across time. We show the superiority of our deep learning model for the task of classifying people with Parkinson's disease as distinct from healthy controls.
Assuntos
Doença de Parkinson , Voz , Humanos , Doença de Parkinson/diagnóstico , Reprodutibilidade dos Testes , Fonação , Aprendizado de MáquinaRESUMO
BACKGROUND: No study has compared pharmacologic properties of ticagrelor and clopidogrel in non-dialysis patients with stage 4-5 chronic kidney disease (CKD). METHODS: We conducted a double-blind RCT to compare effects of ticagrelor and clopidogrel in 48 CKD, with the primary outcome of ADP-induced platelet aggregation (WBPA) after 2 weeks of DAPT. In a parallel arm, we compared effects of 2 weeks of ticagrelor plus aspirin on mean changes in WBPA and markers of thromboinflammation among non-CKD controls (n = 26) with that of CKD in the ticagrelor-arm. RESULTS: Average age of CKD was 53.7 years, with 62% women, 54% African American, and 42% with stage 5 CKD. Ticagrelor generated statistically lower WBPA values post treatment [median 0 Ω (IQR 0, 2)] vs. clopidogrel [median 0 Ω (IQR 0, 5)] (P = 0.002); percent inhibition of WBPA was greater (87 ± 22% vs. 63 ± 50%; P = 0.04; and plasma IL-6 levels were much lower (8.42 ± 1.73 pg/ml vs. 18.48 ± 26.56 pg/ml; P = 0.04). No differences in mean changes in WBPA between CKD-ticagrelor and control groups were observed. Ticagrelor- DAPT reduced levels of IL-1α and IL-1ß in CKD-ticagrelor and control groups, attenuated lowering of TNFα and TRAIL levels in CKD-ticagrelor (vs controls), and had global changes in correlation between various cytokines in a subgroup of CKD-ticagrelor subjects not on statins (n = 10). Peak/trough levels of ticagrelor/metabolite were not different between CKD-ticagrelor and control groups. CONCLUSIONS: We report significant differences in platelet aggregation and anti-inflammatory properties between ticagrelor- and clopidogrel-based DAPT in non-dialysis people with stage 4-5 CKD. These notable inflammatory responses suggest ticagrelor-based DAPT might lower inflammatory burden of asymptomatic patients with stage 4 or 5 CKD. (clinicaltrials.gov # NCT03649711).
Assuntos
Insuficiência Renal Crônica , Trombose , Humanos , Feminino , Pessoa de Meia-Idade , Masculino , Clopidogrel/efeitos adversos , Ticagrelor/efeitos adversos , Agregação Plaquetária , Inibidores da Agregação Plaquetária/uso terapêutico , Inflamação/diagnóstico , Inflamação/tratamento farmacológico , Ticlopidina/efeitos adversos , Adenosina , Insuficiência Renal Crônica/diagnóstico , Insuficiência Renal Crônica/tratamento farmacológico , Resultado do TratamentoRESUMO
Major food crops, such as rice and maize, display severe yield losses (30-50%) under salt stress. Furthermore, problems associated with soil salinity are anticipated to worsen due to climate change. Therefore, it is necessary to implement sustainable agricultural strategies, such as exploiting beneficial plant-microbe associations, for increased crop yields. Plants can develop associations with beneficial microbes, including arbuscular mycorrhiza and plant growth-promoting bacteria (PGPB). PGPB improve plant growth via multiple mechanisms, including protection against biotic and abiotic stresses. Azospirillum brasilense, one of the most studied PGPB, can mitigate salt stress in different crops. However, little is known about the molecular mechanisms by which A. brasilense mitigates salt stress. This study shows that total and root plant mass is improved in A. brasilense-inoculated rice plants compared to the uninoculated plants grown under high salt concentrations (100 mM and 200 mM NaCl). We observed this growth improvement at seven- and fourteen days post-treatment (dpt). Next, we used transcriptomic approaches and identified differentially expressed genes (DEGs) in rice roots when exposed to three treatments: 1) A. brasilense, 2) salt (200 mM NaCl), and 3) A. brasilense and salt (200 mM NaCl), at seven dpt. We identified 786 DEGs in the A. brasilense-treated plants, 4061 DEGs in the salt-stressed plants, and 1387 DEGs in the salt-stressed A. brasilense-treated plants. In the A. brasilense-treated plants, we identified DEGs involved in defense, hormone, and nutrient transport, among others. In the salt-stressed plants, we identified DEGs involved in abscisic acid and jasmonic acid signaling, antioxidant enzymes, sodium and potassium transport, and calcium signaling, among others. In the salt-stressed A. brasilense-treated plants, we identified some genes involved in salt stress response and tolerance (e.g., abscisic acid and jasmonic acid signaling, antioxidant enzymes, calcium signaling), and sodium and potassium transport differentially expressed, among others. We also identified some A. brasilense-specific plant DEGs, such as nitrate transporters and defense genes. Furthermore, our results suggest genes involved in auxin and ethylene signaling are likely to play an important role during these interactions. Overall, our transcriptomic data indicate that A. brasilense improves rice growth under salt stress by regulating the expression of key genes involved in defense and stress response, abscisic acid and jasmonic acid signaling, and ion and nutrient transport, among others. Our findings will provide essential insights into salt stress mitigation in rice by A. brasilense.
RESUMO
Non-legume plants such as rice and maize can form beneficial associations with plant growth-promoting bacteria (PGPB) such as Herbaspirillum seropedicae and Azospirillum brasilense. Several studies have shown that these PGPB promote plant growth via multiple mechanisms. Our current understanding of the molecular aspects and signaling between plants like rice and PGPB like Herbaspirillum seropedicae is limited. In this study, we used an experimental system where H. seropedicae could colonize the plant roots and promote growth in wild-type rice. Using this experimental setup, we identified 1688 differentially expressed genes (DEGs) in rice roots, 1 day post-inoculation (dpi) with H. seropedicae. Several of these DEGs encode proteins involved in the flavonoid biosynthetic pathway, defense, hormone signaling pathways, and nitrate and sugar transport. We validated the expression pattern of some genes via RT-PCR. Next, we compared the DEGs identified in this study to those we previously identified in rice roots during associations with another PGPB, Azospirillum brasilense. We identified 628 genes that were differentially expressed during both associations. The expression pattern of these genes suggests that some of these are likely to play a significant role(s) during associations with both H. seropedicae and A. brasilense and are excellent targets for future studies.
Assuntos
Azospirillum brasilense , Herbaspirillum , Oryza , Azospirillum brasilense/genética , Expressão Gênica , Herbaspirillum/genética , Herbaspirillum/metabolismo , Oryza/genética , Oryza/microbiologia , Raízes de Plantas/metabolismoRESUMO
Background: Chronic kidney disease (CKD) is characterized by dysregulated inflammation that worsens with CKD severity. The role of platelets in modulating inflammation in stage 4 or 5 CKD remains unexplored. We investigated whether there are changes in platelet-derived thromboinflammatory markers in CKD with dual antiplatelet therapy (DAPT; aspirin 81 mg/d plus P2Y12 inhibitor). Methods: In a mechanistic clinical trial, we compared platelet activation markers (aggregation and surface receptor expression), circulating platelet-leukocyte aggregates, leukocyte composition (monocyte subtypes and CD11b surface expression), and plasma cytokine profile (45 analytes) of non-CKD controls (n=26) and CKD outpatients (n=48) with a glomerular filtration rate (GFR) <30 ml/min per 1.73 m2 on 2 weeks of DAPT. Results: Patients with CKD demonstrated a reduced mean platelet count, elevated mean platelet volume, reduced platelet-leukocyte aggregates, reduced platelet-bound monocytes, higher total non-classic monocytes in the circulation, and higher levels of IL-1RA, VEGF, and fractalkine (all P<0.05). There were no differences in platelet activation markers between CKD and controls. Although DAPT reduced platelet aggregation in both groups, it had multifaceted effects on thromboinflammatory markers in CKD, including a reduction in PDGF levels in all CKD individuals, reductions in IL-1ß and TNF-α levels in select CKD individuals, and no change in a number of other cytokines. Significant positive correlations existed for baseline IL-1ß, PDGF, and TNF-α levels with older age, and for baseline TNF-α levels with presence of diabetes mellitus and worse albuminuria. Mean change in IL-1ß and PDGF levels on DAPT positively correlated with younger age, mean change in TNF-α levels with higher GFR, and mean changes in PDGF, and TRAIL levels correlated with worse albuminuria. Minimum spanning trees plot of cytokines showed platelet-derived CD40L had a large reduction in weight factor after DAPT in CKD. Additionally, platelet-derived IL-1ß and PDGF were tightly correlated with other cytokines, with IL-1ß as the hub cytokine. Conclusions: Attenuated interactions between platelets and leukocytes in the CKD state coincided with no change in platelet activation status, an altered differentiation state of monocytes, and heightened inflammatory markers. Platelet-derived cytokines were one of the central cytokines in patients with CKD that were tightly correlated with others. DAPT had multifaceted effects on thromboinflammation, suggesting that there is platelet-dependent and -independent inflammation in stage 4 or 5 CKD.
Assuntos
Insuficiência Renal Crônica , Trombose , Humanos , Albuminúria/tratamento farmacológico , Citocinas , Inflamação/tratamento farmacológico , Inflamação/metabolismo , Inibidores da Agregação Plaquetária/uso terapêutico , Trombose/tratamento farmacológico , Fator de Necrose Tumoral alfaRESUMO
The metaproteome profiling of cecal contents collected from neonatal piglets fed pasteurized human milk (HM) or a dairy-based infant formula (MF) from postnatal day (PND) 2 to 21 were assessed. At PND 21, a subset of piglets from each group (n = 11/group) were euthanized, and cecal contents were collected for further metaproteome analysis. Cecal microbiota composition showed predominantly more Firmicutes phyla and Lachnospiraceae family in the lumen of cecum of HM-fed piglets in comparison to the MF-fed group. Ruminococcus gnavus was the most abundant species from the Firmicutes phyla in the cecal contents of the HM-fed piglets at 21 days of age. A greater number of expressed proteins were identified in the cecal contents of the HM-fed piglets relative to the MF-fed piglets. Greater abundances of proteins potentially expressed by Bacteroides spp. such as glycoside enzymes were noted in the cecal lumen of HM-fed piglets relative to the MF. Additionally, lyases associated with Lachnospiraceae family were abundant in the cecum of the HM group relative to the MF group. Overall, our findings indicate that neonatal diet impacts the gut bacterial taxa and microbial proteins prior to weaning. The metaproteomics data were deposited into PRIDE, PXD025432 and 10.6019/PXD025432.
Assuntos
Dieta , Fórmulas Infantis , Proteoma/metabolismo , Proteômica , Animais , Animais Recém-Nascidos , Bactérias/classificação , Ceco/microbiologia , Microbioma Gastrointestinal , Leite Humano , Modelos Animais , SuínosRESUMO
BACKGROUND: Resistant Starch (RS) improves CKD outcomes. In this report, we study how RS modulates host-microbiome interactions in CKD by measuring changes in the abundance of proteins and bacteria in the gut. In addition, we demonstrate RS-mediated reduction in CKD-induced kidney damage. METHODS: Eight mice underwent 5/6 nephrectomy to induce CKD and eight served as healthy controls. CKD and Healthy (H) groups were further split into those receiving RS (CKDRS, n = 4; HRS, n = 4) and those on normal diet (CKD, n = 4, H, n = 4). Kidney injury was evaluated by measuring BUN/creatinine and by histopathological evaluation. Cecal contents were analyzed using mass spectrometry-based metaproteomics and de novo sequencing using PEAKS. All the data were analyzed using R/Bioconductor packages. RESULTS: The 5/6 nephrectomy compromised kidney function as seen by an increase in BUN/creatinine compared to healthy groups. Histopathology of kidney sections showed reduced tubulointerstitial injury in the CKDRS versus CKD group; while no significant difference in BUN/creatinine was observed between the two CKD groups. Identified proteins point toward a higher population of butyrate-producing bacteria, reduced abundance of mucin-degrading bacteria in the RS fed groups, and to the downregulation of indole metabolism in CKD groups. CONCLUSION: RS slows the progression of chronic kidney disease. Resistant starch supplementation leads to active bacterial proliferation and the reduction of harmful bacterial metabolites.
Assuntos
Microbioma Gastrointestinal/fisiologia , Rim/metabolismo , Insuficiência Renal Crônica/metabolismo , Amido Resistente/metabolismo , Animais , Bactérias/metabolismo , Nitrogênio da Ureia Sanguínea , Modelos Animais de Doenças , Progressão da Doença , Rim/fisiopatologia , Masculino , Camundongos , Insuficiência Renal Crônica/fisiopatologiaRESUMO
BACKGROUND: Acute lymphoblastic leukemia (ALL) is the most common type of cancer diagnosed in children and Glucocorticoids (GCs) form an essential component of the standard chemotherapy in most treatment regimens. The category of infant ALL patients carrying a translocation involving the mixed lineage leukemia (MLL) gene (gene KMT2A) is characterized by resistance to GCs and poor clinical outcome. Although some studies examined GC-resistance in infant ALL patients, the understanding of this phenomenon remains limited and impede the efforts to improve prognosis. METHODS: This study integrates differential co-expression (DC) and protein-protein interaction (PPI) networks to find active protein modules associated with GC-resistance in MLL-rearranged infant ALL patients. A network was constructed by linking differentially co-expressed gene pairs between GC-resistance and GC-sensitive samples and later integrated with PPI networks by keeping the links that are also present in the PPI network. The resulting network was decomposed into two sub-networks, specific to each phenotype. Finally, both sub-networks were clustered into modules using weighted gene co-expression network analysis (WGCNA) and further analyzed with functional enrichment analysis. RESULTS: Through the integration of DC analysis and PPI network, four protein modules were found active under the GC-resistance phenotype but not under the GC-sensitive. Functional enrichment analysis revealed that these modules are related to proteasome, electron transport chain, tRNA-aminoacyl biosynthesis, and peroxisome signaling pathways. These findings are in accordance with previous findings related to GC-resistance in other hematological malignancies such as pediatric ALL. CONCLUSIONS: Differential co-expression analysis is a promising approach to incorporate the dynamic context of gene expression profiles into the well-documented protein interaction networks. The approach allows the detection of relevant protein modules that are highly enriched with DC gene pairs. Functional enrichment analysis of detected protein modules generates new biological hypotheses and may help in explaining the GC-resistance in MLL-rearranged infant ALL patients.
Assuntos
Glucocorticoides/uso terapêutico , Leucemia-Linfoma Linfoblástico de Células Precursoras/tratamento farmacológico , Leucemia-Linfoma Linfoblástico de Células Precursoras/metabolismo , Bases de Dados de Proteínas , Resistencia a Medicamentos Antineoplásicos/genética , Resistencia a Medicamentos Antineoplásicos/fisiologia , Perfilação da Expressão Gênica , Redes Reguladoras de Genes/genética , Redes Reguladoras de Genes/fisiologia , Histona-Lisina N-Metiltransferase/genética , Histona-Lisina N-Metiltransferase/metabolismo , Humanos , Proteína de Leucina Linfoide-Mieloide/genética , Proteína de Leucina Linfoide-Mieloide/metabolismo , Transdução de Sinais/genética , Transdução de Sinais/fisiologiaRESUMO
Gene set analysis (GSA) has become the common methodology for analyzing transcriptomics data. However, self-contained GSA techniques are rarely, if ever, used for proteomics data analysis. Here we present a self-contained proteome level GSA of four consensus molecular subtypes (CMSs) previously established by transcriptome dissection of colon carcinoma specimens. Despite notable difference in structure of proteomics and transcriptomics data, many pathway-wide characteristic features of CMSs found at the mRNA level were reproduced at the protein level. In particular, CMS1 features show heavy involvement of immune system as well as the pathways related to mismatch repair, DNA replication and functioning of proteasome, while CMS4 tumors upregulate complement pathway and proteins participating in epithelial-to-mesenchymal transition (EMT). In addition, protein level GSA yielded a set of novel observations visible at the proteome, but not at the transcriptome level, including possible involvement of major histocompatibility complex II (MHC-II) antigens in the known immunogenicity of CMS1 and a connection between cholesterol trafficking and the regulation of Integrin-linked kinase (ILK) in CMS3. Overall, this study proves utility of self-contained GSA approaches as a critical tool for analyzing proteomics data in general and dissecting protein-level molecular portraits of human tumors in particular.
Assuntos
Neoplasias do Colo/genética , Consenso , Genes Neoplásicos , Proteoma/metabolismo , Transcriptoma/genética , Neoplasias Colorretais/classificação , Neoplasias Colorretais/genética , Matriz Extracelular/metabolismo , Regulação Neoplásica da Expressão Gênica , Redes Reguladoras de Genes , Humanos , Análise de Componente Principal , Transdução de Sinais/genéticaRESUMO
Major non-legume crops can form beneficial associations with nitrogen-fixing bacteria like Azospirillum brasilense. Our current understanding of the molecular aspects and signaling that occur between important crops like rice and these nitrogen-fixing bacteria is limited. In this study, we used an experimental system where the bacteria could colonize the plant roots and promote plant growth in wild type rice and symbiotic mutants (dmi3 and pollux) in rice. Our data suggest that plant growth promotion and root penetration is not dependent on these genes. We then used this colonization model to identify regulation of gene expression at two different time points during this interaction: at 1day post inoculation (dpi), we identified 1622 differentially expressed genes (DEGs) in rice roots, and at 14dpi, we identified 1995 DEGs. We performed a comprehensive data mining to classify the DEGs into the categories of transcription factors (TFs), protein kinases (PKs), and transporters (TRs). Several of these DEGs encode proteins that are involved in the flavonoid biosynthetic pathway, defense, and hormone signaling pathways. We identified genes that are involved in nitrate and sugar transport and are also implicated to play a role in other plant-microbe interactions. Overall, findings from this study will serve as an excellent resource to characterize the host genetic pathway controlling the interactions between non-legumes and beneficial bacteria which can have long-term implications towards sustainably improving agriculture.
Assuntos
Azospirillum brasilense/fisiologia , Oryza/genética , Oryza/microbiologia , Perfilação da Expressão Gênica , Regulação da Expressão Gênica no Desenvolvimento , Regulação da Expressão Gênica de Plantas , Genes de Plantas , Interações entre Hospedeiro e Microrganismos/genética , Modelos Biológicos , Mutação , Oryza/crescimento & desenvolvimento , Raízes de Plantas/genética , Raízes de Plantas/crescimento & desenvolvimento , Raízes de Plantas/microbiologia , RNA de Plantas/genética , RNA-Seq , Transdução de Sinais/genética , Simbiose/genéticaRESUMO
BACKGROUND: Resistant starch is a prebiotic metabolized by the gut bacteria. It has been shown to attenuate chronic kidney disease (CKD) progression in rats. Previous studies employed taxonomic analysis using 16S rRNA sequencing and untargeted metabolomics profiling. Here we expand these studies by metaproteomics, gaining new insight into the host-microbiome interaction. METHODS: Differences between cecum contents in CKD rats fed a diet containing resistant starch with those fed a diet containing digestible starch were examined by comparative metaproteomics analysis. Taxonomic information was obtained using unique protein sequences. Our methodology results in quantitative data covering both host and bacterial proteins. RESULTS: 5,834 proteins were quantified, with 947 proteins originating from the host organism. Taxonomic information derived from metaproteomics data surpassed previous 16S RNA analysis, and reached species resolutions for moderately abundant taxonomic groups. In particular, the Ruminococcaceae family becomes well resolved-with butyrate producers and amylolytic species such as R. bromii clearly visible and significantly higher while fibrolytic species such as R. flavefaciens are significantly lower with resistant starch feeding. The observed changes in protein patterns are consistent with fiber-associated improvement in CKD phenotype. Several known host CKD-associated proteins and biomarkers of impaired kidney function were significantly reduced with resistant starch supplementation. Data are available via ProteomeXchange with identifier PXD008845. CONCLUSIONS: Metaproteomics analysis of cecum contents of CKD rats with and without resistant starch supplementation reveals changes within gut microbiota at unprecedented resolution, providing both functional and taxonomic information. Proteins and organisms differentially abundant with RS supplementation point toward a shift from mucin degraders to butyrate producers.
Assuntos
Proteínas de Bactérias/análise , Ceco/microbiologia , Microbioma Gastrointestinal , Proteoma/análise , Proteômica , Insuficiência Renal Crônica/induzido quimicamente , Ruminococcus , Amido/efeitos adversos , Animais , Progressão da Doença , Masculino , Ratos , Ratos Sprague-Dawley , Insuficiência Renal Crônica/microbiologia , Ruminococcus/classificação , Ruminococcus/crescimento & desenvolvimento , Amido/farmacologiaRESUMO
Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease that leads to the loss of motor neurons. The molecular mechanisms of motor neuron degeneration are largely unknown and there are currently no effective therapies to treat this disease. In this work, we report whole transcriptome profiling of spinal cords of mutant transgenic hPFN1G118V mice and their wildtype transgenic hPFN1WT controls at a pre-symptomatic stage and at the end-stage of disease. Analyses revealed that end-stage hPFN1G118V mice had 890 differentially expressed genes (747 up-regulated, 143 down-regulated) when compared to pre-symptomatic hPFN1G118V mice, and they had 836 differentially expressed genes (742 up-regulated, 94 down-regulated) when compared to age-matched hPFN1WT controls. Pre-symptomatic hPFN1G118V mice were not significantly different from age-matched hPFN1WT controls. Ingenuity Pathway Analysis identified inflammatory pathways significantly activated in end-stage hPFN1G118V samples, suggesting an excess of glial activation at end-stage disease, possibly due to an increase in glial composition within the spinal cord during disease progression. In conclusion, our RNA-Seq data identified molecules and pathways involved in the mechanisms of neurodegeneration that could potentially serve as therapeutic targets for ALS.
Assuntos
Esclerose Lateral Amiotrófica/genética , Doenças Neurodegenerativas/genética , Profilinas/genética , Transcriptoma/genética , Esclerose Lateral Amiotrófica/fisiopatologia , Animais , Modelos Animais de Doenças , Progressão da Doença , Humanos , Camundongos , Camundongos Transgênicos , Neurônios Motores/metabolismo , Neurônios Motores/patologia , Doenças Neurodegenerativas/metabolismo , Doenças Neurodegenerativas/patologia , Neuroglia/metabolismo , Neuroglia/patologia , Análise de Sequência de RNA , Medula Espinal/metabolismo , Medula Espinal/fisiopatologiaRESUMO
BACKGROUND: Sessile serrated adenomas/polyps are distinguished from hyperplastic colonic polyps subjectively by their endoscopic appearance and histological morphology. However, hyperplastic and sessile serrated polyps can have overlapping morphological features resulting in sessile serrated polyps diagnosed as hyperplastic. While sessile serrated polyps can progress into colon cancer, hyperplastic polyps have virtually no risk for colon cancer. Objective measures, differentiating these types of polyps would improve cancer prevention and treatment outcome. METHODS: RNA-seq training data set and Affimetrix, Illumina testing data sets were obtained from Gene Expression Omnibus (GEO). RNA-seq single-end reads were filtered with FastX toolkit. Read mapping to the human genome, gene abundance estimation, and differential expression analysis were performed with Tophat-Cufflinks pipeline. Background correction, normalization, and probe summarization steps for Affimetrix arrays were performed using the robust multi-array method (RMA). For Illumina arrays, log2-scale expression data was obtained from GEO. Pathway analysis was implemented using Bioconductor package GSAR. To build a platform-independent molecular classifier that accurately differentiates sessile serrated and hyperplastic polyps we developed a new feature selection step. We also developed a simple procedure to classify new samples as either sessile serrated or hyperplastic with a class probability assigned to the decision, estimated using Cantelli's inequality. RESULTS: The classifier trained on RNA-seq data and tested on two independent microarray data sets resulted in zero and three errors. The classifier was further tested using quantitative real-time PCR expression levels of 45 blinded independent formalin-fixed paraffin-embedded specimens and was highly accurate. Pathway analyses have shown that sessile serrated polyps are distinguished from hyperplastic polyps and normal controls by: up-regulation of pathways implicated in proliferation, inflammation, cell-cell adhesion and down-regulation of serine threonine kinase signaling pathway; differential co-expression of pathways regulating cell division, protein trafficking and kinase activities. CONCLUSIONS: Most of the differentially expressed pathways are known as hallmarks of cancer and likely to explain why sessile serrated polyps are more prone to neoplastic transformation than hyperplastic. The new molecular classifier includes 13 genes and may facilitate objective differentiation between two polyps.
Assuntos
Adenoma/patologia , Neoplasias do Colo/patologia , Pólipos do Colo/patologia , Transcriptoma , Adenoma/classificação , Adenoma/genética , Algoritmos , Proteínas Quinases Dependentes de Cálcio-Calmodulina/genética , Proteínas de Ciclo Celular/genética , Análise por Conglomerados , Neoplasias do Colo/classificação , Neoplasias do Colo/genética , Pólipos do Colo/classificação , Pólipos do Colo/genética , Bases de Dados Genéticas , Regulação para Baixo , Proteínas de Ligação ao GTP/genética , Redes Reguladoras de Genes , Humanos , Hiperplasia/classificação , Hiperplasia/genética , Hiperplasia/patologia , Peptídeos e Proteínas de Sinalização Intracelular/genética , Proteínas de Neoplasias/genética , Proteínas de Ligação a Poli-ADP-Ribose/genética , Análise de Componente Principal , Ubiquitina-Proteína Ligases/genética , Regulação para CimaRESUMO
The Musashi family of RNA binding proteins act to promote stem cell self-renewal and oppose cell differentiation predominantly through translational repression of mRNAs encoding pro-differentiation factors and inhibitors of cell cycle progression. During tissue development and repair however, Musashi repressor function must be dynamically regulated to allow cell cycle exit and differentiation. The mechanism by which Musashi repressor function is attenuated has not been fully established. Our prior work indicated that the Musashi1 isoform undergoes site-specific regulatory phosphorylation. Here, we demonstrate that the canonical Musashi2 isoform is subject to similar regulated site-specific phosphorylation, converting Musashi2 from a repressor to an activator of target mRNA translation. We have also characterized a novel alternatively spliced, truncated isoform of human Musashi2 (variant 2) that lacks the sites of regulatory phosphorylation and fails to promote translation of target mRNAs. Consistent with a role in opposing cell cycle exit and differentiation, upregulation of Musashi2 variant 2 was observed in a number of cancers and overexpression of the Musashi2 variant 2 isoform promoted cell transformation. These findings indicate that alternately spliced isoforms of the Musashi protein family possess distinct functional and regulatory properties and suggest that differential expression of Musashi isoforms may influence cell fate decisions.
Assuntos
Regulação da Expressão Gênica , Processamento de Proteína Pós-Traducional , Proteínas de Ligação a RNA/metabolismo , Animais , Linhagem Celular , Humanos , Fosforilação , Isoformas de Proteínas/metabolismoRESUMO
The analysis of gene sets (in a form of functionally related genes or pathways) has become the method of choice for extracting the strongest signals from omics data. The motivation behind using gene sets instead of individual genes is two-fold. First, this approach incorporates pre-existing biological knowledge into the analysis and facilitates the interpretation of experimental results. Second, it employs a statistical hypotheses testing framework. Here, we briefly review main Gene Set Analysis (GSA) approaches for testing differential expression of gene sets and several GSA approaches for testing statistical hypotheses beyond differential expression that allow extracting additional biological information from the data. We distinguish three major types of GSA approaches testing: (1) differential expression (DE), (2) differential variability (DV), and (3) differential co-expression (DC) of gene sets between two phenotypes. We also present comparative power analysis and Type I error rates for different approaches in each major type of GSA on simulated data. Our evaluation presents a concise guideline for selecting GSA approaches best performing under particular experimental settings. The value of the three major types of GSA approaches is illustrated with real data example. While being applied to the same data set, major types of GSA approaches result in complementary biological information.
Assuntos
Biologia Computacional/métodos , Redes Reguladoras de Genes , Simulação por Computador , Mineração de Dados , Expressão Gênica , Perfilação da Expressão Gênica , Genômica , Humanos , Análise de Sequência com Séries de Oligonucleotídeos , FenótipoRESUMO
BACKGROUND: Gene set analysis (in a form of functionally related genes or pathways) has become the method of choice for analyzing omics data in general and gene expression data in particular. There are many statistical methods that either summarize gene-level statistics for a gene set or apply a multivariate statistic that accounts for intergene correlations. Most available methods detect complex departures from the null hypothesis but lack the ability to identify the specific alternative hypothesis that rejects the null. RESULTS: GSAR (Gene Set Analysis in R) is an open-source R/Bioconductor software package for gene set analysis (GSA). It implements self-contained multivariate non-parametric statistical methods testing a complex null hypothesis against specific alternatives, such as differences in mean (shift), variance (scale), or net correlation structure. The package also provides a graphical visualization tool, based on the union of two minimum spanning trees, for correlation networks to examine the change in the correlation structures of a gene set between two conditions and highlight influential genes (hubs). CONCLUSIONS: Package GSAR provides a set of multivariate non-parametric statistical methods that test a complex null hypothesis against specific alternatives. The methods in package GSAR are applicable to any type of omics data that can be represented in a matrix format. The package, with detailed instructions and examples, is freely available under the GPL (> = 2) license from the Bioconductor web site.
Assuntos
Biologia Computacional/métodos , Bases de Dados Genéticas , Perfilação da Expressão Gênica , Software , Linhagem Celular Tumoral , Expressão Gênica , Humanos , Modelos Teóricos , Análise Multivariada , Fenótipo , Análise de Sequência de RNA , Proteína Supressora de Tumor p53/genética , Proteína Supressora de Tumor p53/metabolismoRESUMO
PURPOSE: Despite vast improvements that have been made in the treatment of children with acute lymphoblastic leukemia (ALL), the majority of infant ALL patients (~80 %, < 1 year of age) that carry a chromosomal translocation involving the mixed lineage leukemia (MLL) gene shows a poor response to chemotherapeutic drugs, especially glucocorticoids (GCs), which are essential components of all current treatment regimens. Although addressed in several studies, the mechanism(s) underlying this phenomenon have remained largely unknown. A major drawback of most previous studies is their primary focus on individual genes, thereby neglecting the putative significance of inter-gene correlations. Here, we aimed at studying GC resistance in MLL-rearranged infant ALL patients by inferring an associated module of genes using co-expression network analysis. The implications of newly identified candidate genes with associations to other well-known relevant genes from the same module, or with associations to known transcription factor or microRNA interactions, were substantiated using literature data. METHODS: A weighted gene co-expression network was constructed to identify gene modules associated with GC resistance in MLL-rearranged infant ALL patients. Significant gene ontology (GO) terms and signaling pathways enriched in relevant modules were used to provide guidance towards which module(s) consisted of promising candidates suitable for further analysis. RESULTS: Through gene co-expression network analysis a novel set of genes (module) related to GC-resistance was identified. The presence in this module of the S100 and ANXA genes, both well-known biomarkers for GC resistance in MLL-rearranged infant ALL, supports its validity. Subsequent gene set net correlation analyses of the novel module provided further support for its validity by showing that the S100 and ANXA genes act as 'hub' genes with potentially major regulatory roles in GC sensitivity, but having lost this role in the GC resistant phenotype. The detected module implicates new genes as being candidates for further analysis through associations with known GC resistance-related genes. CONCLUSIONS: From our data we conclude that available systems biology approaches can be employed to detect new candidate genes that may provide further insights into drug resistance of MLL-rearranged infant ALL cases. Such approaches complement conventional gene-wise approaches by taking putative functional interactions between genes into account.
Assuntos
Antineoplásicos/uso terapêutico , Resistencia a Medicamentos Antineoplásicos/genética , Perfilação da Expressão Gênica/métodos , Glucocorticoides/uso terapêutico , Leucemia-Linfoma Linfoblástico de Células Precursoras/tratamento farmacológico , Leucemia-Linfoma Linfoblástico de Células Precursoras/genética , Redes Reguladoras de Genes , Histona-Lisina N-Metiltransferase/genética , Humanos , Lactente , Proteína de Leucina Linfoide-Mieloide/genéticaRESUMO
The microbial diversity within cave ecosystems is largely unknown. Ozark caves maintain a year-round stable temperature (12-14 °C), but most parts of the caves experience complete darkness. The lack of sunlight and geological isolation from surface-energy inputs generate nutrient-poor conditions that may limit species diversity in such environments. Although microorganisms play a crucial role in sustaining life on Earth and impacting human health, little is known about their diversity, ecology, and evolution in community structures. We used five Ozark region caves as test sites for exploring bacterial diversity and monitoring long-term biodiversity. Illumina MiSeq sequencing of five cave soil samples and a control sample revealed a total of 49 bacterial phyla, with seven major phyla: Proteobacteria, Acidobacteria, Actinobacteria, Firmicutes, Chloroflexi, Bacteroidetes, and Nitrospirae. Variation in bacterial composition was observed among the five caves studied. Sandtown Cave had the lowest richness and most divergent community composition. 16S rRNA gene-based metagenomic analysis of cave-dwelling microbial communities in the Ozark caves revealed that species abundance and diversity are vast and included ecologically, agriculturally, and economically relevant taxa.
RESUMO
Helicases are enzymes involved in nucleic acid metabolism, playing major roles in replication, transcription, and repair. Defining helicases oligomerization state and transient and persistent protein interactions is essential for understanding of their function. In this article we review current methods for the protein-protein interaction analysis, and discuss examples of its application to the study of helicases: Pif1 and DDX3. Proteomics methods are our main focus - affinity pull-downs and chemical cross-linking followed by mass spectrometry. We review advantages and limitations of these methods and provide general guidelines for their implementation in the functional analysis of helicases.
Assuntos
DNA Helicases/genética , Replicação do DNA/genética , Mapeamento de Interação de Proteínas/métodos , Mapas de Interação de Proteínas/genética , DNA Helicases/química , Reparo do DNA/genéticaRESUMO
Transcriptome sequencing (RNA-seq) is gradually replacing microarrays for high-throughput studies of gene expression. The main challenge of analyzing microarray data is not in finding differentially expressed genes, but in gaining insights into the biological processes underlying phenotypic differences. To interpret experimental results from microarrays, gene set analysis (GSA) has become the method of choice, in particular because it incorporates pre-existing biological knowledge (in a form of functionally related gene sets) into the analysis. Here we provide a brief review of several statistically different GSA approaches (competitive and self-contained) that can be adapted from microarrays practice as well as those specifically designed for RNA-seq. We evaluate their performance (in terms of Type I error rate, power, robustness to the sample size and heterogeneity, as well as the sensitivity to different types of selection biases) on simulated and real RNA-seq data. Not surprisingly, the performance of various GSA approaches depends only on the statistical hypothesis they test and does not depend on whether the test was developed for microarrays or RNA-seq data. Interestingly, we found that competitive methods have lower power as well as robustness to the samples heterogeneity than self-contained methods, leading to poor results reproducibility. We also found that the power of unsupervised competitive methods depends on the balance between up- and down-regulated genes in tested gene sets. These properties of competitive methods have been overlooked before. Our evaluation provides a concise guideline for selecting GSA approaches, best performing under particular experimental settings in the context of RNA-seq.