Biology subjects

Shrestha, R.

Publications and source records attributed to Shrestha, R..

8 recordsLinked to original sources

bioRxiv2018

The requirement for the amino acid co-germinant during C. difficile spore germination is influenced by mutations in yabG and cspA

Clostridium difficile spore germination is critical for the transmission of disease. C. difficile spores germinate in response to cholic acid derivatives, such as taurocholate (TA), and amino acids, such as glycine or alanine. Although the bile acid germinant receptor is known, the amino acid germinant receptor has remained elusive. Here, we used EMS mutagenesis to generate mutants with altered requirements for the amino acid co-germinant, similar to the strategy used previously to identify the bile acid receptor, CspC. Surprisingly, we identified strains that do not require amino acids as co-germinants, and the mutant spores germinated in response to TA alone. Upon sequencing these mutants, we identified different mutations in yabG. In C. difficile, yabG expression is required for the processing of CspBA to CspB and CspA and preproSleC to proSleC during spore formation. A defined yabG mutant exacerbated the EMS mutant phenotype. Moreover, we found that various mutations in cspA caused spores to germinate in the presence of TA alone without the requirement of an amino acid. Thus, our study provides evidence that apart from regulating the CspC levels in the spore, CspA is important for recognition of amino acids as co-germinants during C. difficile spore germination and that two pseudoproteases (CspC and CspA) function as the C. difficile germinant receptors.

microbiology↗

bioRxiv2018

Pathway and network analysis of more than 2,500 whole cancer genomes

The catalog of cancer driver mutations in protein-coding genes has greatly expanded in the past decade. However, non-coding cancer driver mutations are less well-characterized and only a handful of recurrent non-coding mutations, most notably TERT promoter mutations, have been reported. Motivated by the success of pathway and network analyses in prioritizing rare mutations in protein-coding genes, we performed multi-faceted pathway and network analyses of non-coding mutations across 2,583 whole cancer genomes from 27 tumor types compiled by the ICGC/TCGA PCAWG project. While few non-coding genomic elements were recurrently mutated in this cohort, we identified 93 genes harboring non-coding mutations that cluster into several modules of interacting proteins. Among these are promoter mutations associated with reduced mRNA expression in TP53, TLE4, and TCF4. We found that biological processes had variable proportions of coding and non-coding mutations, with chromatin remodeling and proliferation pathways altered primarily by coding mutations, while developmental pathways, including Wnt and Notch, altered by both coding and non-coding mutations. RNA splicing was primarily targeted by non-coding mutations in this cohort, with samples containing non-coding mutations exhibiting similar gene expression signatures as coding mutations in well-known RNA splicing factors. These analyses contribute a new repertoire of possible cancer genes and mechanisms that are altered by non-coding mutations and offer insights into additional cancer vulnerabilities that can be investigated for potential therapeutic treatments.

cancer biology↗

bioRxiv2018

Combinatorial Detection of Conserved Alteration Patterns for Identifying Cancer Subnetworks

BackgroundAdvances in large scale tumor sequencing have lead to an understanding that there are combinations of genomic and transcriptomic alterations speciflc to tumor types, shared across many patients. Unfortunately, computational identiflcation of functionally meaningful shared alteration patterns, impacting gene/protein interaction subnetworks, has proven to be challenging. FindingsWe introduce a novel combinatorial method, cd-CAP, for simultaneous detection of connected subnetworks of an interaction network where genes exhibit conserved alteration patterns across tumor samples. Our method differentiates distinct alteration types associated with each gene (rather than relying on binary information of a gene being altered or not), and simultaneously detects multiple alteration proflle conserved subnetworks. ConclusionsIn a number of The Cancer Genome Atlas (TCGA) data sets, cd-CAP identifled large biologically signiflcant subnetworks with conserved alteration patterns, shared across many tumor samples.

systems biology↗

bioRxiv2018

DNMT1 in Six2 progenitor cells is essential for transposable element silencing and kidney development

Cytosine methylation (5mC) plays a key role in maintaining progenitor cell self-renewal and differentiation. Here, we analyzed the role of 5mC in kidney development by genome-wide methylation, expression profiling, and by systematic genetic targeting of DNA methyltransferases (Dnmt) and Ten-eleven translocation methylcytosine hydroxylases (Tet).\n\nIn mice, nephrons differentiate from Six2+ progenitor cells, therefore we created animals with genetic deletion of Dnmt1, 3a, 3b, Tet1, and Tet2 in the Six2+ population (Six2Cre/Dnmt1flox/flox, Six2Cre/Dnmt3aflox/flox, Six2Cre/Dnmt3bflox/flox, Six2Cre/Tet2flox/flox and Tet1-/-). Animals with conditional deletion of Dnmt3a, 3b, Tet1 and Tet2 showed no significant structural or functional renal abnormalities. On the other hand, Six2Cre/Dnmt1flox/flox mice died within 24hrs of birth. Dnmt1 knock-out animals had small kidneys and significantly reduced nephron number. Genome-wide methylation analysis indicated marked loss of methylation mostly on transposable elements. RNA sequencing detected endogenous retroviral (ERV) gene transcripts and early embryonic genes. Increase in levels of interferon (and RIG-I signaling) and apoptosis (Trp53) in response to ERV activity likely contributed to the phenotype development. Once epithelial differentiation was established, loss of Dnmt1, 3a, 3b, Tet1 or Tet2 in glomerular epithelial cells did not lead to functional or structural differences at baseline or following toxic glomerular injury.\n\nGenome-wide cytosine methylation and gene expression profiling showed that Dnmt1-mediated DNA methylation is essential for kidney development by preventing regression of progenitor cells into a primitive undifferentiated state and demethylation of transposable elements.\n\nSignificanceCytosine methylation of regulatory regions (promoters and enhancers) has been proposed to play a key role in establishing gene expression and thereby cellular phenotype. DNMT1 is the key enzyme responsible for maintaining methylation patterns during DNA replication. While the role of Dnmt1 has been described in multiple organs, here we identified a novel, critically important mechanism how Dnmt1 controls tissue progenitors. The greatest methylation difference in Dnmt1 knock-out mice was observed on transposable elements (TE), which resulted in increase of endogenous retroviruses and cell death. We believe that release of TE was a critically overlooked component of phenotype development in previous studies that our comprehensive genome wide methylation analysis allowed us to identify.\n\nCompeting interestsThe Susztak lab receives research support from Biogen, Boehringer Ingelheim, Celgene, GSK, Merck, Regeneron and ONO Pharma for work not related to this manuscript.

developmental biology↗

bioRxiv2018

BAP1 Loss Predicts Therapeutic Vulnerability in Malignant Peritoneal Mesothelioma

BackgroundMalignant Peritoneal Mesothelioma (PeM) is a rare but frequently fatal cancer that originates from the peritoneal lining of the abdomen. Standard treatment of PeM is limited to cytoreductive surgery and/or chemotherapy, and no effective targeted therapies for PeM yet exist. In the search for novel therapeutic target candidates in PeM, we performed a comprehensive integrative multi-omics analysis of 19 treatment-naive PeM tumors.\n\nResultsThe analysis identified PeM tumors with BAP1 loss to form a distinct molecular subtype characterized by distinct expression patterns of genes involved in chromatin remodeling, DNA repair pathway, and immune checkpoint receptor activation. This PeM subtype could potentially benefit from immune checkpoint, PARP, or HDAC inhibition therapies.\n\nConclusionsOur findings uncover BAP1 as a trackable prognostic and predictive biomarker, and refine PeM disease classification. This integrated molecular characterization provides a comprehensive foundation for developing PeM precision medicine.

cancer biology↗

bioRxiv2018

Deep Genomic Signature for early metastasis prediction in prostate cancer

For prostate cancer patients, timing and intensity of therapy are adjusted based on their prognosis. Clinical and pathological factors, and recently, gene expression-based signatures have been shown to predict metastatic prostate cancer. Previous studies used labelled datasets, i.e. those with information on the metastasis outcome, to discover gene signatures to predict metastasis. Due to steady progression of prostate cancer, datasets for this cancer have a limited number of labelled samples but more unlabelled samples. In addition to this issue, the high dimensionality of the gene expression data also poses a significant challenge to train a classifier and predict metastasis accurately. In this study, we aim to boost the prediction accuracy by utilizing both labelled and unlabelled datasets together. We propose Deep Genomic Signature (DGS), a method based on Denoising Auto-Encoders (DAEs) and transfer learning. DGS has the following steps: first, we train a DAE on a large unlabelled gene expression dataset to extract the most salient features of its samples. Then, we train another DAE on a small labelled dataset for a similar purpose. Since the labelled dataset is small, we employ a transfer learning approach and use the parameters learned from the first DAE in the second one. This approach enables us to train a large DAE on a small dataset. After training the second DAE, we obtain the list of genes with high weights by applying a standard deviation filter on the transferred and learned weights. Finally, we train an elastic net logistic regression model on the expression of the selected genes to predict metastasis. Because of the elastic net regularization, some of the selected genes have non-zero coefficients in the classifier which we consider as the DGS gene signature for metastasis. We apply DGS to six labelled and one large unlabelled prostate cancer datasets. Results on five validation datasets indicate that DGS outperforms state-of-the-art gene signatures (obtained from only labelled datasets) in terms of prediction accuracy. Survival analyses demonstrate the potential clinical utility of our gene signature that adds novel prognostic information to the well-established clinical factors and the state-of-the-art gene signatures. Finally, pathway analysis reveals that the DGS gene signature captures the hallmarks of prostate cancer metastasis. These results suggest that our method helps to identify a robust gene signature that may improve patient management.

bioinformatics↗

bioRxiv2017

Comprehensive single cell RNAseq analysis of the kidney reveals novel cell types and unexpected cell plasticity

A key limitations to understand kidney function and disease development has been that specific cell types responsible for specific homeostatic kidney function or disease phenotypes have not been defined at the molecular level.\n\nTo fill this gap, we characterized 57,979 cells from healthy mouse kidneys using unbiased single-cell RNA sequencing. We show that genetic mutations that present with similar phenotypes mostly affect genes that are expressed in a single unique differentiated cell type. On the other hand, we found unexpected cell plasticity of epithelial cells in the final segment of the kidney (collecting duct) that is responsible for final composition of the urine. Using computational cell trajectory analysis and in vivo linage tracing, we found that, intercalated cells (that secrete protons) and principal cells (that maintain salt, water and potassium balance) undergo a Notch mediated interconversion via a newly identified transitional cell type. In disease states this transition is shifted towards the principal cell fate. Loss of intercalated cells likely contributes to metabolic acidosis observed in kidney disease.\n\nIn summary, single cell analysis advanced a mechanistic description of kidney diseases by identifying a defective homeostatic cell lineage.\n\nOne Sentence SummaryA comprehensive single cell atlas of the kidney reveals a transitional cell type and cell plasticity determined by Notch signaling which is defective in chronic kidney disease.

cell biology↗

bioRxiv2017

Effects Of Curcumin Nanoformulations On Cellular Function In Niemann-Pick Disease Type C Astrocytes

Niemann-Pick disease type C1 (NPC disease) is a neurodegenerative multi-lipid lysosomal storage disease caused by mutations in the NPC1 gene presenting with reduced lysosomal Ca2+ signalling and inhibited late endosome-lysosome transport. Elevating cytosolic Ca2+ levels in NPC cells has been shown to reduce lysosomal lipid storage. Treating Npc1-/- mice with the Ca2+ modulator curcumin led to reduced lipid storage, improved life expectancy and function. These studies led to reported utilisation of curcumin supplements by NPC disease families despite there being no clinical evidence of benefit and a report indicating no benefit of nanoformulated curcumin in Npc1-/- mice. The aim of this study was to determine whether various commercially available curcumin nanoformulations were capable of reproducing the findings obtained with unformulated pharmaceutical grade curcumin. We compared seven curcumin nanoformulations in Npc1-/- mouse astrocytes. All the nanoformulations elevate cytosolic Ca2+ levels but only two lowered lysosomal lipid storage. Importantly, some caused elevations in NPC lysosomal storage and/or decreased cellular viability. Although this is an in vitro study, our findings suggest that care should be taken when contemplating the use of curcumin supplements for NPC disease.

pharmacology and toxicology↗