Single cell genomics-based analysis of gene content and expression of prophages in a diffuse-flow deep-sea hydrothermal system

© The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Labonte, J. M., Pachiadaki, M., Fergusson, E., McNichol, J., Grosche, A., Gulmann, L. K., Vetriani, C., Sievert, S. M., & Stepanauskas, R. Single cell genomics-based analysis of gene content and expression of prophages in a diffuse-flow deep-sea hydrothermal system. Frontiers in Microbiology, 10, (2019): 1262, doi:10.3389/fmicb.2019.01262.Phage–host interactions likely play a major role in the composition and functioning of many microbiomes, yet remain poorly understood. Here, we employed single cell genomics to investigate phage–host interactions in a diffuse-flow, low-temperature hydrothermal vent that may be reflective of a broadly distributed biosphere in the subseafloor. We identified putative prophages in 13 of 126 sequenced single amplified genomes (SAGs), with no evidence for lytic infections, which is in stark contrast to findings in the surface ocean. Most were distantly related to known prophages, while their hosts included bacterial phyla Campylobacterota, Bacteroidetes, Chlorobi, Proteobacteria, Lentisphaerae, Spirochaetes, and Thermotogae. Our results suggest the predominance of lysogeny over lytic interaction in diffuse-flow, deep-sea hydrothermal vents, despite the high activity of the dominant Campylobacteria that would favor lytic infections. We show that some of the identified lysogens have co-evolved with their host over geological time scales and that their genes are transcribed in the environment. Functional annotations of lysogeny-related genes suggest involvement in horizontal gene transfer enabling host’s protection against toxic metals and antibacterial compounds.This work was supported by the U.S. National Science Foundation’s Dimensions of Biodiversity Program [OCE-1136488 (to RS), OCE-1136727 (to SMS) and OCE-1136451 (to CV)], as well as DEB-1441717 and OCE-1335810 (to RS), and the DOE JGI CSP project 1477

Comparative kinome analysis to identify putative colon tumor biomarkers

Kinase domains are the type of protein domain most commonly found in genes associated with tumorigenesis. Because of this, the human kinome (the protein kinase component of the genome) represents a promising source of cancer biomarkers and potential targets for novel anti-cancer therapies. Alterations in the human colon kinome during the progression from normal colon (NC) through adenoma (AD) to adenocarcinoma (AC) were investigated using integrated transcriptomic and proteomic datasets. Two hundred thirty kinase genes and 42 kinase proteins showed differential expression patterns (fold change ≥ 1.5) in at least one tissue pair-wise comparison (AD vs. NC, AC vs. NC, and/or AC vs. AD). Kinases that exhibited similar trends in expression at both the mRNA and protein levels were further analyzed in individual samples of NC (n = 20), AD (n = 39), and AC (n = 24) by quantitative reverse transcriptase PCR. Individual samples of NC and tumor tissue were distinguishable based on the mRNA levels of a set of 20 kinases. Altered expression of several of these kinases, including chaperone activity of bc1 complex-like (CABC1) kinase, bromodomain adjacent to zinc finger domain protein 1B (BAZ1B) kinase, calcium/calmodulin-dependent protein kinase type II subunit delta (CAMK2D), serine/threonine-protein kinase 24 (STK24), vaccinia-related kinase 3 (VRK3), and TAO kinase 3 (TAOK3), has not been previously reported in tumor tissue. These findings may have diagnostic potential and may lead to the development of novel targeted therapeutic interventions for colorectal cancer

Integrative MicroRNA and Proteomic Approaches Identify Novel Osteoarthritis Genes and Their Collaborative Metabolic and Inflammatory Networks

BACKGROUND: Osteoarthritis is a multifactorial disease characterized by destruction of the articular cartilage due to genetic, mechanical and environmental components affecting more than 100 million individuals all over the world. Despite the high prevalence of the disease, the absence of large-scale molecular studies limits our ability to understand the molecular pathobiology of osteoathritis and identify targets for drug development. METHODOLOGY/PRINCIPAL FINDINGS: In this study we integrated genetic, bioinformatic and proteomic approaches in order to identify new genes and their collaborative networks involved in osteoarthritis pathogenesis. MicroRNA profiling of patient-derived osteoarthritic cartilage in comparison to normal cartilage, revealed a 16 microRNA osteoarthritis gene signature. Using reverse-phase protein arrays in the same tissues we detected 76 differentially expressed proteins between osteoarthritic and normal chondrocytes. Proteins such as SOX11, FGF23, KLF6, WWOX and GDF15 not implicated previously in the genesis of osteoarthritis were identified. Integration of microRNA and proteomic data with microRNA gene-target prediction algorithms, generated a potential "interactome" network consisting of 11 microRNAs and 58 proteins linked by 414 potential functional associations. Comparison of the molecular and clinical data, revealed specific microRNAs (miR-22, miR-103) and proteins (PPARA, BMP7, IL1B) to be highly correlated with Body Mass Index (BMI). Experimental validation revealed that miR-22 regulated PPARA and BMP7 expression and its inhibition blocked inflammatory and catabolic changes in osteoarthritic chondrocytes. CONCLUSIONS/SIGNIFICANCE: Our findings indicate that obesity and inflammation are related to osteoarthritis, a metabolic disease affected by microRNA deregulation. Gene network approaches provide new insights for elucidating the complexity of diseases such as osteoarthritis. The integration of microRNA, proteomic and clinical data provides a detailed picture of how a network state is correlated with disease and furthermore leads to the development of new treatments. This strategy will help to improve the understanding of the pathogenesis of multifactorial diseases such as osteoarthritis and provide possible novel therapeutic targets

Discovery of New Molecular Subtypes in Oesophageal Adenocarcinoma

A large number of patients suffering from oesophageal adenocarcinomas do not respond to conventional chemotherapy; therefore, it is necessary to identify new predictive biomarkers and patient signatures to improve patient outcomes and therapy selections. We analysed 87 formalin-fixed and paraffin-embedded (FFPE) oesophageal adenocarcinoma tissue samples with a reverse phase protein array (RPPA) to examine the expression of 17 cancer-related signalling molecules. Protein expression levels were analysed by unsupervised hierarchical clustering and correlated with clinicopathological parameters and overall patient survival. Proteomic analyses revealed a new, very promising molecular subtype of oesophageal adenocarcinoma patients characterised by low levels of the HSP27 family proteins and high expression of those of the HER family with positive lymph nodes, distant metastases and short overall survival. After confirmation in other independent studies, our results could be the foundation for the development of a Her2-targeted treatment option for this new patient subgroup of oesophageal adenocarcinoma

Integrative MicroRNA and Proteomic Approaches Identify Novel Osteoarthritis Genes and Their Collaborative Metabolic and Inflammatory Networks

BACKGROUND: Osteoarthritis is a multifactorial disease characterized by destruction of the articular cartilage due to genetic, mechanical and environmental components affecting more than 100 million individuals all over the world. Despite the high prevalence of the disease, the absence of large-scale molecular studies limits our ability to understand the molecular pathobiology of osteoathritis and identify targets for drug development. METHODOLOGY/PRINCIPAL FINDINGS: In this study we integrated genetic, bioinformatic and proteomic approaches in order to identify new genes and their collaborative networks involved in osteoarthritis pathogenesis. MicroRNA profiling of patient-derived osteoarthritic cartilage in comparison to normal cartilage, revealed a 16 microRNA osteoarthritis gene signature. Using reverse-phase protein arrays in the same tissues we detected 76 differentially expressed proteins between osteoarthritic and normal chondrocytes. Proteins such as SOX11, FGF23, KLF6, WWOX and GDF15 not implicated previously in the genesis of osteoarthritis were identified. Integration of microRNA and proteomic data with microRNA gene-target prediction algorithms, generated a potential "interactome" network consisting of 11 microRNAs and 58 proteins linked by 414 potential functional associations. Comparison of the molecular and clinical data, revealed specific microRNAs (miR-22, miR-103) and proteins (PPARA, BMP7, IL1B) to be highly correlated with Body Mass Index (BMI). Experimental validation revealed that miR-22 regulated PPARA and BMP7 expression and its inhibition blocked inflammatory and catabolic changes in osteoarthritic chondrocytes. CONCLUSIONS/SIGNIFICANCE: Our findings indicate that obesity and inflammation are related to osteoarthritis, a metabolic disease affected by microRNA deregulation. Gene network approaches provide new insights for elucidating the complexity of diseases such as osteoarthritis. The integration of microRNA, proteomic and clinical data provides a detailed picture of how a network state is correlated with disease and furthermore leads to the development of new treatments. This strategy will help to improve the understanding of the pathogenesis of multifactorial diseases such as osteoarthritis and provide possible novel therapeutic targets

Update for the practicing pathologist: The International Consultation On Urologic Disease-European association of urology consultation on bladder cancer

The International Consultations on Urological Diseases are international consensus meetings, supported by the World Health Organization and the Union Internationale Contre le Cancer, which have occurred since 1981. Each consultation has the goal of convening experts to review data and provide evidence-based recommendations to improve practice. In 2012, the selected subject was bladder cancer, a disease which remains a major public health problem with little improvement in many years. The proceedings of the 2nd International Consultation on Bladder Cancer, which included a 'Pathology of Bladder Cancer Work Group,' have recently been published; herein, we provide a summary of developments and consensus relevant to the practicing pathologist. Although the published proceedings have tackled a comprehensive set of issues regarding the pathology of bladder cancer, this update summarizes the recommendations regarding selected issues for the practicing pathologist. These include guidelines for classification and grading of urothelial neoplasia, with particular emphasis on the approach to inverted lesions, the handling of incipient papillary lesions frequently seen during surveillance of bladder cancer patients, descriptions of newer variants, and terminology for urine cytology reporting

A BAFF-R mutation associated with non-Hodgkin lymphoma alters TRAF recruitment and reveals new insights into BAFF-R signaling

A BAFF receptor mutation associated with non-Hodgkin lymphoma provides new insight into the proximal players of normal BAFF-R signaling

Trends in the incidence of adenocarcinoma of the oesophagus and cardia in the Netherlands 1989–2003

Over the 15-year period 1989–2003, the incidence of oesophagus–cardia adenocarcinoma in the Netherlands rose annually by 2.6% for males and 1.2% for females. This was the net outcome of annual increases in the incidence of adenocarcinoma of the oesophagus (ACO) of 7.2% for males and 3.5% for females and annual declines in the incidence of adenocarcinoma of the gastric cardia (AGC) of more than 1% for both genders. Nonlinear cohort patterns were found in females with ACO and for both genders in AGC; a nonlinear period pattern was observed only in males with AGC. These differing epidemiological patterns for ACO and AGC do not support a common aetiology. Proposed underlying factors for the rise in ACO incidence appear to have little effect on AGC incidence. This and the secular decline in smoking among males may have led to the decline in AGC incidence

Genomic and oncoproteomic advances in detection and treatment of colorectal cancer

<p>Abstract</p> <p>Aims</p> <p>We will examine the latest advances in genomic and proteomic laboratory technology. Through an extensive literature review we aim to critically appraise those studies which have utilized these latest technologies and ascertain their potential to identify clinically useful biomarkers.</p> <p>Methods</p> <p>An extensive review of the literature was carried out in both online medical journals and through the Royal College of Surgeons in Ireland library.</p> <p>Results</p> <p>Laboratory technology has advanced in the fields of genomics and oncoproteomics. Gene expression profiling with DNA microarray technology has allowed us to begin genetic profiling of colorectal cancer tissue. The response to chemotherapy can differ amongst individual tumors. For the first time researchers have begun to isolate and identify the genes responsible. New laboratory techniques allow us to isolate proteins preferentially expressed in colorectal cancer tissue. This could potentially lead to identification of a clinically useful protein biomarker in colorectal cancer screening and treatment.</p> <p>Conclusion</p> <p>If a set of discriminating genes could be used for characterization and prediction of chemotherapeutic response, an individualized tailored therapeutic regime could become the standard of care for those undergoing systemic treatment for colorectal cancer. New laboratory techniques of protein identification may eventually allow identification of a clinically useful biomarker that could be used for screening and treatment. At present however, both expression of different gene signatures and isolation of various protein peaks has been limited by study size. Independent multi-centre correlation of results with larger sample sizes is needed to allow translation into clinical practice.</p