Identification of cancer subtypes from single-cell RNA-seq data using a consensus clustering method

Background

Human cancers are complex ecosystems composed of cells with distinct molecular signatures. Such intratumoral heterogeneity poses a major challenge to cancer diagnosis and treatment. Recent advancements of single-cell techniques such as scRNA-seq have brought unprecedented insights into cellular heterogeneity. Subsequently, a challenging computational problem is to cluster high dimensional noisy datasets with substantially fewer cells than the number of genes.

Methods

In this paper, we introduced a consensus clustering framework conCluster, for cancer subtype identification from single-cell RNA-seq data. Using an ensemble strategy, conCluster fuses multiple basic partitions to consensus clusters.

Results

Applied to real cancer scRNA-seq datasets, conCluster can more accurately detect cancer subtypes than the widely used scRNA-seq clustering methods. Further, we conducted co-expression network analysis for the identified melanoma subtypes.

Conclusions

Our analysis demonstrates that these subtypes exhibit distinct gene co-expression networks and significant gene sets with different functional enrichment.

     

Plant growth-promoting bacterium <Emphasis Type="Italic">Pseudomonas fluorescens</Emphasis> FR1 secrets a novel type of extracellular polyhydroxybutyrate polymerase involved in abiotic stress response in plants

Objectives

Identification of novel microbial factors contributing to plant protection against abiotic stress.

Results

The genome of plant growth-promoting bacterium Pseudomonas fluorescens FR1 contains a short mobile element encoding a novel type of extracellular polyhydroxybutyrate (PHB) polymerase (PhbC) associated with a type I secretion system. Genetic analysis using a phbC mutant strain and plants showed that this novel extracellular enzyme is related to the PHB production in planta and suggests that PHB could be a beneficial microbial compound synthesized during plant adaptation to cold stress.

Conclusion

Extracellular PhbC can be used as a new tool for improve crop production under abiotic stress.

     

Expression of the entire polyhydroxybutyrate operon of <Emphasis Type="Italic">Ralstonia eutropha</Emphasis> in plants

Background

Previously we demonstrated that an entire bacterial operon (the PRN operon) is expressible in plants when driven by the Tomato -yellow-leaf-curl-virus (TYLCV) -derived universal vector IL-60.Petroleum-derived plastics are not degradable, and are therefore harmful to the environment. Fermentation of bacteria carrying operons for polyhydroxyalkanoates (PHAs) produces degradable bioplastics which are environmentally friendly. However, bacterial production of bioplastics is not cost-effective, and attention is turning to their production in plants. Such “green” plastics would be less expensive and environmentally friendly. Hence, attempts are being made to substitute petroleum-derived plastics with “green” plastics. However, transformation of plants with genes of operons producing bioplastics has deleterious effects. Transformation of plastids does not cause deleterious effects, however it is a complicated procedures.

Results

We have developed another TYLCV-based vector (SE100) and show that yet another bacterial operon (the phaCAB operon) when driven by SE100 is also expressed in plants. We employed the combination of SE100 and the phaCAB operon to drive the operon to the plastids and produce in plants a biodegradable plastic [polyhydroxybutyrate (PHB)].Here we indicate that the bacterial operon (phaCAB), when driven by the newly developed universal plant vector SE100 is directed to chloroplasts and produces in plants PHB, a leading PHA. The PHB-producing plants circumvent the need for complicated technical procedures.

Conclusion

The viral vector system SE100 facilitated the production of the bio-plastic poly-3-hydroxybutyrate. This was achieved by using the full pha-CAB operon indicating that TYLCV based system can transcribe and translate genes from bacterial operons controlled by a single cis element. Our data hints to the participation of the chloroplasts in these processes.

     

Identification of glioblastoma gene prognosis modules based on weighted gene co-expression network analysis

Background

Glioblastoma multiforme, the most prevalent and aggressive brain tumour, has a poor prognosis. The molecular mechanisms underlying gliomagenesis remain poorly understood. Therefore, molecular research, including various markers, is necessary to understand the occurrence and development of glioma.

Method

Weighted gene co-expression network analysis (WGCNA) was performed to construct a gene co-expression network in TCGA glioblastoma samples. Gene ontology (GO) and pathway-enrichment analysis were used to identify significance of gene modules. Cox proportional hazards regression model was used to predict outcome of glioblastoma patients.

Results

We performed weighted gene co-expression network analysis (WGCNA) and identified a gene module (yellow module) related to the survival time of TCGA glioblastoma samples. Then, 228 hub genes were calculated based on gene significance (GS) and module significance (MS). Four genes (OSMR + SOX21?+?MED10?+?PTPRN) were selected to construct a Cox proportional hazards regression model with high accuracy (AUC?=?0.905). The prognostic value of the Cox proportional hazards regression model was also confirmed in GSE16011 dataset (GBM: n?=?156).

Conclusion

We developed a promising mRNA signature for estimating overall survival in glioblastoma patients.

     

Identification of biomarkers of chromophobe renal cell carcinoma by weighted gene co-expression network analysis

Background

Chromophobe renal cell carcinoma (ChRCC) is the second common subtype of non-clear cell renal cell carcinoma (nccRCC), which accounting for 4–5% of renal cell carcinoma (RCC). However, there is no effective bio-marker to predict clinical outcomes of this malignant disease. Bioinformatic methods may provide a feasible potential to solve this problem.

Methods

In this study, differentially expressed genes (DEGs) of ChRCC samples on The Cancer Genome Atlas database were filtered out to construct co-expression modules by weighted gene co-expression network analysis and the key module were identified by calculating module-trait correlations. Functional analysis was performed on the key module and candidate hub genes were screened out by co-expression and MCODE analysis. Afterwards, real hub genes were filter out in an independent dataset GSE15641 and validated by survival analysis.

Results

Overall 2215 DEGs were screened out to construct eight co-expression modules. Brown module was identified as the key module for the highest correlations with pathologic stage, neoplasm status and survival status. 29 candidate hub genes were identified. GO and KEGG analysis demonstrated most candidate genes were enriched in mitotic cell cycle. Three real hub genes (SKA1, ERCC6L, GTSE-1) were selected out after mapping candidate genes to GSE15641 and two of them (SKA1, ERCC6L) were significantly related to overall survivals of ChRCC patients.

Conclusions

In summary, our findings identified molecular markers correlated with progression and prognosis of ChRCC, which might provide new implications for improving risk evaluation, therapeutic intervention, and prognosis prediction in ChRCC patients.

     

In vivo phosphorylation of a peptide tag for protein purification

Objectives

To design a new system for the in vivo phosphorylation of proteins in Escherichia coli using the co-expression of the α-subunit of casein kinase II (CKIIα) and a target protein, (Nanofitin) fused with a phosphorylatable tag.

Results

The level of the co-expressed CKIIα was controlled by the arabinose promoter and optimal phosphorylation was obtained with 2 % (w/v) arabinose as inductor. The effectiveness of the phosphorylation system was demonstrated by electrophoretic mobility shift assay (NUT-PAGE) and staining with a specific phosphoprotein-staining gel. The resulting phosphorylated tag was also used to purify the phosphoprotein by immobilized metal affinity chromatography, which relies on the specific interaction of phosphate moieties with Fe(III).

Conclusion

The use of a single tag for both the purification and protein array anchoring provides a simple and straightforward system for protein analysis.

     

Secretion of polyhydroxybutyrate in <Emphasis Type="Italic">Escherichia coli</Emphasis> using a synthetic biological engineering approach

Background

Polyhydroxyalkanoates (PHAs) are a group of biodegradable plastics that are produced by a wide variety of microorganisms, mainly as a storage intermediate for energy and carbon. Polyhydroxybutyrate (PHB) is a short-chain-length PHA with interesting chemical and physical properties. Large scale production of PHB is not wide-spread mainly due to the downstream processing of bacterial cultures to extract the PHB. Secretion of PHB from Escherichia coli could reduce downstream processing costs. PHB are non-proteinaceous polymers, hence cannot be directly targeted for secretion. Phasin, PhaP1, is a low molecular weight protein that binds to PHB, reducing PHB granule size. In this study PHB is indirectly secreted with PhaP1 from E. coli via type I secretion using HlyA signal peptides.

Results

This study demonstrated the successful secretion of phasin and phasin bound PHB outside of the cell and into the culture medium. The secretion of PHB was initiated between 24 and 48 h after induction. After 48 h of culturing, 36% of the total PHB produced in the secreting strain was collected in the secreted fraction and 64% remained in the internal fraction. To further support the findings of this study, the PHB secretion phenomenon was observed using SEM.

Conclusions

From this study, the ability to use type I secretion to: 1) secrete phasin and 2) successfully secrete PHB has been shown.

     

A network based covariance test for detecting multivariate eQTL in saccharomyces cerevisiae

Background

Expression quantitative trait locus (eQTL) analysis has been widely used to understand how genetic variations affect gene expressions in the biological systems. Traditional eQTL is investigated in a pair-wise manner in which one SNP affects the expression of one gene. In this way, some associated markers found in GWAS have been related to disease mechanism by eQTL study. However, in real life, biological process is usually performed by a group of genes. Although some methods have been proposed to identify a group of SNPs that affect the mean of gene expressions in the network, the change of co-expression pattern has not been considered. So we propose a process and algorithm to identify the marker which affects the co-expression pattern of a pathway. Considering two genes may have different correlations under different isoforms which is hard to detect by the linear test, we also consider the nonlinear test.

Results

When we applied our method to yeast eQTL dataset profiled under both the glucose and ethanol conditions, we identified a total of 166 modules, with each module consisting of a group of genes and one eQTL where the eQTL regulate the co-expression patterns of the group of genes. We found that many of these modules have biological significance.

Conclusions

We propose a network based covariance test to identify the SNP which affects the structure of a pathway. We also consider the nonlinear test as considering two genes may have different correlations under different isoforms which is hard to detect by linear test.

     

Optimization of fecal sample preparation for untargeted LC-HRMS based metabolomics

Introduction

Collecting feces is easy. It offers direct outcome to endogenous and microbial metabolites.

Objectives

In a context of lack of consensus about fecal sample preparation, especially in animal species, we developed a robust protocol allowing untargeted LC-HRMS fingerprinting.

Methods

The conditions of extraction (quantity, preparation, solvents, dilutions) were investigated in bovine feces.

Results

A rapid and simple protocol involving feces extraction with methanol (1/3, M/V) followed by centrifugation and a step filtration (10 kDa) was developed.

Conclusion

The workflow generated repeatable and informative fingerprints for robust metabolome characterization.

     

Rapid extraction and purification of lumbrokinase from <Emphasis Type="Italic">Lumbricus rubellus</Emphasis> using a hollow fiber membrane and size exclusion chromatography

Objectives

To develop a purification process using hollow fiber membrane separation combined with size exclusion chromatography for the extraction of lumbrokinase from earthworms (Lumbricus rubellus).

Results

To extract the protein, the earthworms were first homogenized for 10 min, to produce ultrafine particles. Polyether sulfone hollow fiber membranes with MW cut offs of 50 and 6 kDa were used for initial purification of the crude extract. Further purification was carried out on a Sephadex G-75 column, and yielded three fractions of high purity protein. One of these fractions showed fibrinolytic activity.

Conclusions

Three samples of high purity protein were obtained and one protein (LK1) showed strong fibrinolytic activity. The method has higher purification efficiency in comparison with existing methods.

     

Identifying functional relationships within sets of co-expressed genes by combining upstream regulatory motif analysis and gene expression information

Background

Existing clustering approaches for microarray data do not adequately differentiate between subsets of co-expressed genes. We devised a novel approach that integrates expression and sequence data in order to generate functionally coherent and biologically meaningful subclusters of genes. Specifically, the approach clusters co-expressed genes on the basis of similar content and distributions of predicted statistically significant sequence motifs in their upstream regions.

Results

We applied our method to several sets of co-expressed genes and were able to define subsets with enrichment in particular biological processes and specific upstream regulatory motifs.

Conclusions

These results show the potential of our technique for functional prediction and regulatory motif identification from microarray data.

     

A lost opportunity for science: journals promote data sharing in metabolomics but do not enforce it

Introduction

Data sharing is being increasingly required by journals and has been heralded as a solution to the ‘replication crisis’.

Objectives

(i) Review data sharing policies of journals publishing the most metabolomics papers associated with open data and (ii) compare these journals’ policies to those that publish the most metabolomics papers.

Methods

A PubMed search was used to identify metabolomics papers. Metabolomics data repositories were manually searched for linked publications.

Results

Journals that support data sharing are not necessarily those with the most papers associated to open metabolomics data.

Conclusion

Further efforts are required to improve data sharing in metabolomics.

     

The role of laterally transferred genes in adaptive evolution

Background

Bacterial genomes develop new mechanisms to tide them over the imposing conditions they encounter during the course of their evolution. Acquisition of new genes by lateral gene transfer may be one of the dominant ways of adaptation in bacterial genome evolution. Lateral gene transfer provides the bacterial genome with a new set of genes that help it to explore and adapt to new ecological niches.

Methods

A maximum likelihood analysis was done on the five sequenced corynebacterial genomes to model the rates of gene insertions/deletions at various depths of the phylogeny.

Results

The study shows that most of the laterally acquired genes are transient and the inferred rates of gene movement are higher on the external branches of the phylogeny and decrease as the phylogenetic depth increases. The newly acquired genes are under relaxed selection and evolve faster than their older counterparts. Analysis of some of the functionally characterised LGTs in each species has indicated that they may have a possible adaptive role.

Conclusion

The five Corynebacterial genomes sequenced to date have evolved by acquiring between 8 – 14% of their genomes by LGT and some of these genes may have a role in adaptation.

     

Purification of therapeutic proteins mediated by in vivo polyester immobilized sortase

Objectives

To overcome laborious and costly procedures often associated with therapeutic protein production and purification, in vivo polyester immobilized sortase is explored for the production of human tumor necrosis factor alpha (TNFα) and human interferon alpha 2b (IFNα2b) by Escherichia coli.

Results

Hybrid genes encoding PhaC-Sortase-TNFα or PhaC-Sortase-IFNα2b fusions (with a LPETG recognition signal immediately before TNFα or IFNα2b), mediated intracellular production of polyester (polyhydroxyalkanoate, PHA) beads in Escherichia coli. Upon isolation of respective PHA beads, pure soluble TNFα or IFNα2b was released by activating sortase via addition of CaCl₂ and triglycine. TNFα and IFNα2b each were recognized by corresponding conformational antibodies in an ELISA assay.

Conclusions

In vivo polyester immobilized sortase could be exploited for production and purification of high-value therapeutic proteins without laborious and costly downstream processing.

     

Integrated analysis of microRNA-target interactions with clinical outcomes for cancers

Background

Clinical statement alone is not enough to predict the progression of disease. Instead, the gene expression profiles have been widely used to forecast clinical outcomes. Many genes related to survival have been identified, and recently miRNA expression signatures predicting patient survival have been also investigated for several cancers. However, miRNAs and their target genes associated with clinical outcomes have remained largely unexplored.

Methods

Here, we demonstrate a survival analysis based on the regulatory relationships of miRNAs and their target genes. The patient survivals for the two major cancers, ovarian cancer and glioblastoma multiforme (GBM), are investigated through the integrated analysis of miRNA-mRNA interaction pairs.

Results

We found that there is a larger survival difference between two patient groups with an inversely correlated expression profile of miRNA and mRNA. It supports the idea that signatures of miRNAs and their targets related to cancer progression can be detected via this approach.

Conclusions

This integrated analysis can help to discover coordinated expression signatures of miRNAs and their target mRNAs that can be employed for therapeutics in human cancers.

     

Pseudo current density maps of electrophysiological heart,nerve or brain function and their physical basis

Background

In recent years the visualization of biomagnetic measurement data by so-called pseudo current density maps or Hosaka-Cohen (HC) transformations became popular.

Methods

The physical basis of these intuitive maps is clarified by means of analytically solvable problems.

Results

Examples in magnetocardiography, magnetoencephalography and magnetoneurography demonstrate the usefulness of this method.

Conclusion

Hardware realizations of the HC-transformation and some similar transformations are discussed which could advantageously support cross-platform comparability of biomagnetic measurements.

     

High level soluble expression and one-step purification of IBDV VP2 protein in <Emphasis Type="Italic">Escherichia coli</Emphasis>

Objectives

To improve the expression of soluble IBDV VP2 protein by using different tagged vectors in Escherichia coli.

Results

Fusion tags, Grifin, MBP, SUMO, thioredoxin, γ-crystallin, ArsC and PpiB, enhanced the expression and solubility of VP2 protein. The fusion proteins were purified by Ni–NTA chromatography, MBP-VP2 showed the highest purity about 90 %. After removing the MBP tag, VP2 self-assembled into virus-like particles, ~25 nm diam. Results from AGP suggested the recombinant IBDV VP2 protein identified by reference serum like IBDV.

Conclusion

All the seven tags enhanced the expression and solubility of IBDV VP2 protein. The recombinant protein self-assembly into virus like particles and possess antigenicity as reference IBDV.